Systems and techniques for estimating eye pose

ABSTRACT

An eye tracking system can include an eye-tracking camera configured to obtain images of the eye at different exposure times or different frame rates. For example, longer exposure images of the eye taken at a longer exposure time can show iris or pupil features, and shorter exposure, glint images can show peaks of glints reflected from the cornea. The shorter exposure glint images may be taken at a higher frame rate (than the longer exposure images) for accurate gaze prediction. The shorter exposure glint images can be analyzed to provide glint locations to subpixel accuracy. The longer exposure images can be analyzed for pupil center or center of rotation. The eye tracking system can predict future gaze direction, which can be used for foveated rendering by a wearable display system. In some instances, the eye-tracking system may estimate the location of a partially or totally occluded glint.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. Patent Application No.17/659,145 filed Apr. 13, 2022, titled SYSTEMS AND TECHNIQUES FORESTIMATING EYE POSE, which is a continuation of U.S. Patent ApplicationNo. 16/878,366 filed May 19, 2020, titled SYSTEMS AND TECHNIQUES FORESTIMATING EYE POSE, which claims the benefit of priority to U.S. PatentApplication No. 62/850,539, filed May 20, 2019, titled SYSTEMS ANDTECHNIQUES FOR ESTIMATING EYE POSE. The entire contents of each of theabove-identified patent applications are hereby incorporated byreference herein.

This application also incorporates by reference the entirety of each ofthe following patent applications and publications: U.S. PatentApplication No. 15/159,491 filed on May 19, 2016, published on Nov. 24,2016 as U.S. Patent Application Publication No. 2016/0344957; U.S.Patent Application No. 15/717,747 filed on Sep. 27, 2017, published onApr. 5, 2018 as U.S. Patent Application Publication No. 2018/0096503;U.S. Patent Application No. 15/803,351 filed on Nov. 3, 2017, publishedon May 10, 2018 as U.S. Patent Application Publication No. 2018/0131853;U.S. Patent Application No. 15/841,043 filed on Dec. 13, 2017, publishedon Jun. 28, 2018 as U.S. Patent Application Publication No.2018/0183986; U.S. Patent Application No. 15/925,577 filed on Mar. 19,2018, published on Sep. 27, 2018 as U.S. Patent Application PublicationNo. 2018/0278843; U.S. Provisional Patent Application No. 62/660,180,filed on Apr. 19, 2018; U.S. Patent Application No. 16/219,829 filed onDec. 13, 2018, published on Jun. 13, 2019 as U.S. Patent ApplicationPublication No. 2019/0181171; U.S. Patent Application No. 16/219,847filed on Dec. 13, 2018, published on Jun. 13, 2019 as U.S. PatentApplication Publication No. 2019/0181169; U.S. Patent Application No.16/250,931 filed on Jan. 17, 2019, published on Aug. 8, 2019 as U.S.Patent Application Publication No. 2019/0243448; U.S. Patent ApplicationNo. 16/251,017, filed Jan. 17, 2019, published on Jul. 18, 2019 as U.S.Patent Application Publication No. 2019/0222830; U.S. Provisional PatentApplication No. 62/797,072, filed on Jan. 25, 2019; and U.S. PatentApplication No. 16/751,076, filed on Jan. 23, 2020.

FIELD

The present disclosure relates to display systems, virtual reality, andaugmented reality imaging and visualization systems and, moreparticularly, to techniques for tracking a user’s eyes in such systems.

BACKGROUND

Modern computing and display technologies have facilitated thedevelopment of systems for so called “virtual reality”, “augmentedreality”, or “mixed reality” experiences, wherein digitally reproducedimages or portions thereof are presented to a user in a manner whereinthey seem to be, or may be perceived as, real. A virtual reality, or“VR”, scenario typically involves presentation of digital or virtualimage information without transparency to other actual real-world visualinput; an augmented reality, or “AR”, scenario typically involvespresentation of digital or virtual image information as an augmentationto visualization of the actual world around the user; a mixed reality,or “MR”, related to merging real and virtual worlds to produce newenvironments where physical and virtual objects co-exist and interact inreal time. As it turns out, the human visual perception system is verycomplex, and producing a VR, AR, or MR technology that facilitates acomfortable, natural-feeling, rich presentation of virtual imageelements amongst other virtual or real-world imagery elements ischallenging. Systems and methods disclosed herein address variouschallenges related to VR, AR and MR technology.

SUMMARY

An eye tracking system can include an eye-tracking camera configured toobtain images of the eye at different exposure times or different framerates. For example, images of the eye taken at a longer exposure timecan show iris or pupil features, and images of the eye taken at shorterexposure times (sometimes referred to as glint images) can show peaks ofglints reflected from the cornea. The shorter exposure glint images maybe taken at a higher frame rate (HFR) than the longer exposure images toprovide for accurate gaze prediction. The shorter exposure glint imagescan be analyzed to provide glint locations to subpixel accuracy. Thelonger exposure images can be analyzed for pupil center or center ofrotation. The eye tracking system can predict future gaze direction,which can be used for foveated rendering by a wearable display system,for example, an AR, VR, or MR wearable display system.

In various embodiments, the exposure time of the longer exposure imagemay be in a range from 200 µs to 1200 µs, for example, about 700 µs. Thelonger exposure images can be taken at a frame rate in a range from 10frames per second (fps) to 60 fps (e.g., 30 fps), 30 fps to 60 fps, orsome other range. The exposure time of the shorter exposure, glintimages may be in a range from 5 µs to 100 µs, for example, less thanabout 40 µs. The ratio of the exposure time for the longer exposureimage relative to the exposure time for the glint image can be in arange from 5 to 50, 10 to 20, or some other range. The glint images canbe taken at a frame rate in a range from 50 fps to 1000 fps (e.g., 120fps), 200 fps to 400 fps, or some other range in various embodiments.The ratio of the frame rate for the glint images relative to the framerate for the longer exposure images can be in a range from 1 to 100, 1to 50, 2 to 20, 3 to 10, or some other ratio.

In some embodiments, the shorter exposure images are analyzed by a firstprocessor (which may be disposed in or on a head-mounted component ofthe wearable display system), and the longer exposure images areanalyzed by a second processor (which may be disposed in or on anon-head mounted component of the wearable display system, such as,e.g., a beltpack). In some embodiments, the first processor comprises abuffer in which portions of the shorter exposure images are temporarilystored for determining glint location(s).

Details of one or more implementations of the subject matter describedin this specification are set forth in the accompanying drawings and thedescription below. Other features, aspects, and advantages will becomeapparent from the description, the drawings, and the claims. Neitherthis summary nor the following detailed description purports to defineor limit the scope of the inventive subject matter.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts an illustration of a mixed reality scenario with certainvirtual reality objects, and certain physical objects viewed by aperson.

FIG. 2 schematically illustrates an example of a wearable system.

FIG. 3 schematically illustrates example components of a wearablesystem.

FIG. 4 schematically illustrates an example of a waveguide stack of awearable device for outputting image information to a user.

FIG. 5 schematically illustrates an example of an eye.

FIG. 5A schematically illustrates an example coordinate system fordetermining an eye pose of an eye.

FIG. 6 is a schematic diagram of an example of a wearable system thatincludes an eye tracking system, which can implement embodiments of themultiple exposure time eye tracking techniques described herein.

FIG. 7 is a block diagram of an example of a wearable system thatincludes an eye tracking system, which can implement embodiments of themultiple exposure time eye tracking techniques described herein.

FIG. 8A is a schematic diagram of a cross-section of an eye showing theeye’s corneal sphere, optical axis, and gaze. Optical sources illuminatethe eye, and reflections of the optical sources from the cornea (glints)can be imaged by a camera for eye tracking.

FIG. 8B is a photograph of an eye showing an example of four glints.

FIGS. 9A, 9B, and 9C schematically illustrate examples of types oferrors that can occur in measurement of the eye optical axis or gaze.

FIG. 10A shows an example of glints and determination of glint positionusing a longer exposure image.

FIG. 10B shows an example of glints in a longer exposure image and ashorter exposure, glint image. The glint position may be determined moreaccurately from the glint image than from the longer exposure image.

FIG. 11 shows an example of a combined operational mode of aneye-tracking system in which longer exposure images are taken at a firstframe rate, and shorter exposure glint images are taken at a secondframe, which may, in some embodiments, be higher than the first framerate.

FIG. 12 schematically illustrates an example of how the use of shortexposure glint images, which may be captured at high frame rates, canprovide robust glint detection and tracking as the eye moves.

FIG. 13A is a schematic diagram of a cross-section of an eye showing theeye’s corneal sphere. Optical sources illuminate the eye, andreflections of the optical sources from the cornea (glints) can beimaged by the cameras for eye tracking. Glints from reflections from twolight sources can be used to accurately model the cornea modeled center.A glint from reflection from another light source is from anon-spherical portion of the cornea and its use in modeling the corneacenter may lead to error.

FIG. 13B is an image that shows an example of a glint where there ispartial occlusion of the eye.

FIGS. 14A and 14B are graphs of examples of glint movement versus pupilmovement in a Cartesian (x,y) coordinate system, with the x-axis beinghorizontal and the y-axis being vertical.

FIG. 15 schematically illustrates an example of foveated rendering.

FIG. 16 schematically illustrates an example timing diagram for arendering pipeline, which utilizes an embodiment of long and shortexposure imaging for eye tracking.

FIG. 17 is a block diagram of an example gaze prediction system forfoveated rendering, which utilizes an embodiment of long and shortimaging for eye tracking and prediction of future gaze direction.

FIGS. 18A, 18B, 18C, and 18D illustrate results of an experiment topredict future gaze using an embodiment of the gaze prediction systemshown in FIG. 17 .

FIG. 19 is a flowchart that illustrates an example method for eyetracking.

FIG. 20 is a flowchart that illustrates an example method for glintestimation.

Throughout the drawings, reference numbers may be re-used to indicatecorrespondence between referenced elements. Unless indicated otherwise,the drawings are schematic and not necessarily drawn to scale. Thedrawings are provided to illustrate example embodiments described hereinand are not intended to limit the scope of the disclosure.

DETAILED DESCRIPTION Overview

A wearable display system such as, e.g., an AR, MR, or VR display systemcan track the user’s eyes in order to project virtual content towardwhere the user is looking. An eye tracking system can include aninward-facing, eye-tracking camera, and light sources (e.g., infraredlight emitting diodes) that provide reflections (called glints) from theuser’s corneas. A processor can analyze images of the user’s eyes takenby the eye-tracking camera to obtain positions of the glints and othereye features (e.g., the pupil or iris) and determine eye gaze from theglints and eye features.

Eye images that are sufficient to show not only the glints but also theeye features may be taken with relatively long exposure times (e.g.,several hundred to a thousand µs). However, the glints may be saturatedin such longer exposure images, which can make it challenging toaccurately identify the position of the glint center. For example, anuncertainty in the glint position may be 10 to 20 pixels, which canintroduce a corresponding error in the gaze direction of about 20 to 50arcminutes.

Accordingly, various embodiments of the eye tracking systems describedherein obtain images of the eye at different exposure times or atdifferent frame rates. For example, longer exposure images of the eyetaken at a longer exposure time can show iris or pupil features, andshorter exposure images can show peaks of glints reflected from thecornea. The shorter exposure images are sometimes referred to herein asglint images, because they may be used to identify coordinate positionsof glints in the images. The shorter exposure glint images may, in someimplementations, be taken at a high frame rate (HFR) for accurate gazeprediction (e.g., a frame rate that is higher than the frame rate forthe longer exposure images). The shorter exposure glint images can beanalyzed to provide glint locations to subpixel accuracy leading toaccurate predictions of gaze direction (e.g., to within a few arcminutesor better). The longer exposure images can be analyzed for pupil centeror center of rotation.

In some implementations, at least a portion of a glint image istemporarily stored in a buffer and that portion of the glint image isanalyzed to identify positions of one or more glints that may be locatedin that portion. For example, the portion may comprise a relativelysmall number of pixels, rows, or columns of the glint image. In somecases, the portion may comprise an n x m portion of the glint image,where n and m are integers that can be in a range from about 1 to 20.After the positions of the glint(s) are identified, the buffer may becleared. An additional portion of the glint image may then be stored inthe buffer for analysis, until either the entire glint image has beenprocessed or all the glints (commonly, four) have been identified. Theglint positions (e.g., Cartesian coordinates) may be used for subsequentactions in the eye-tracking process, and after the glint positions havebeen stored or communicated to a suitable processor, the glint image maybe deleted from memory (buffer memory or other volatile or non-volatilestorage). Such buffering may advantageously permit rapid processing ofthe glint image to identify glint positions or reduce storage needs ofthe eye-tracking process since the glint image may be deleted after use.

Accordingly, in certain embodiments, the shorter exposure images are notcombined with the longer exposure images to obtain a high dynamic range(HDR) image that is used for eye tracking. Rather, in some suchembodiments, the shorter exposure images and the longer exposure imagesare processed separately and are used to determine differentinformation. For example, the shorter exposure image may be used foridentifying glint positions (e.g., coordinates of the glint centers) oreye gaze direction. The shorter exposure image may be deleted frommemory (e.g., a buffer) after the glint positions are determined. Thelonger exposure images may be used for determining pupil center orcenter of rotation, extract iris features for biometric securityapplications, determine eyelid shape or occlusion of the iris or pupilby the eyelid, measure pupil size, determine render camera parameters,and so forth. In some implementations, different processors perform theprocessing of the shorter and longer exposure images. For example, aprocessor in the head-mounted display may process the shorter exposureimages, and a processor in a non-head mounted unit (e.g., a beltpack)may process the longer exposure images.

Thus, various embodiments of the multiple exposure time techniquesdescribed herein can reap the benefits of HDR luminosity that iscollectively provided by both the shorter and longer exposure images,without combining, compositing, merging, or otherwise processing suchshort and long exposure images together (e.g., as an HDR image). Assuch, various embodiments of the multiple exposure eye tracking systemdo not use such short and long exposure images to generate or otherwiseobtain HDR images.

In various embodiments, the exposure time of the longer exposure imagemay be in a range from 200 µs to 1200 µs, for example, about 700 µs. Thelonger exposure images can be taken at a frame rate in a range from 10frames per second (fps) to 60 fps (e.g., 30 fps), 30 fps to 60 fps, orsome other range. The exposure time of the glint images may be in arange from 5 µs to 100 µs, for example, less than about 40 µs. The ratioof the exposure time for the longer exposure image relative to theexposure time for the shorter exposure glint image can be in a rangefrom 5 to 50, 10 to 20, or some other range. The glint images can betaken at a frame rate in a range from 50 fps to 1000 fps (e.g., 120fps), 200 fps to 400 fps, or some other range in various embodiments.The ratio of the frame rate for the glint images relative to the framerate for the longer exposure images can be in a range from 1 to 100, 1to 50, 2 to 20, 3 to 10, or some other ratio.

Some wearable systems may utilize foveated rendering techniques in whichvirtual content may be rendered primarily in the direction the user islooking. Embodiments of the eye tracking system can accurately estimatefuture gaze direction (e.g., out to about 50 ms in the future), whichcan be used by the rendering system to prepare virtual content forfuture rendering, and which may advantageously reduce rendering latencyand improve user experience.

Examples of 3D Display of a Wearable System

A wearable system (also referred to herein as an augmented reality (AR)system) can be configured to present 2D or 3D virtual images to a user.The images may be still images, frames of a video, or a video, incombination or the like. At least a portion of the wearable system canbe implemented on a wearable device that can present a VR, AR, or MRenvironment, alone or in combination, for user interaction. The wearabledevice can be used interchangeably as an AR device (ARD). Further, forthe purpose of the present disclosure, the term “AR” is usedinterchangeably with the term “MR”.

FIG. 1 depicts an illustration of a mixed reality scenario with certainvirtual reality objects, and certain physical objects viewed by aperson. In FIG. 1 , an MR scene 100 is depicted wherein a user of an MRtechnology sees a real-world park-like setting 110 featuring people,trees, buildings in the background, and a concrete platform 120. Inaddition to these items, the user of the MR technology also perceivesthat he “sees” a robot statue 130 standing upon the real-world platform120, and a cartoon-like avatar character 140 flying by which seems to bea personification of a bumble bee, even though these elements do notexist in the real world.

In order for the 3D display to produce a true sensation of depth, andmore specifically, a simulated sensation of surface depth, it may bedesirable for each point in the display’s visual field to generate anaccommodative response corresponding to its virtual depth. If theaccommodative response to a display point does not correspond to thevirtual depth of that point, as determined by the binocular depth cuesof convergence and stereopsis, the human eye may experience anaccommodation conflict, resulting in unstable imaging, harmful eyestrain, headaches, and, in the absence of accommodation information,almost a complete lack of surface depth.

VR, AR, and MR experiences can be provided by display systems havingdisplays in which images corresponding to a plurality of depth planesare provided to a viewer. The images may be different for each depthplane (e.g., provide slightly different presentations of a scene orobject) and may be separately focused by the viewer’s eyes, therebyhelping to provide the user with depth cues based on the accommodationof the eye required to bring into focus different image features for thescene located on different depth plane or based on observing differentimage features on different depth planes being out of focus. Asdiscussed elsewhere herein, such depth cues provide credible perceptionsof depth.

FIG. 2 illustrates an example of wearable system 200 which can beconfigured to provide an AR/VR/MR scene. The wearable system 200 canalso be referred to as the AR system 200. The wearable system 200includes a display 220, and various mechanical and electronic modulesand systems to support the functioning of display 220. The display 220may be coupled to a frame 230, which is wearable by a user, wearer, orviewer 210. The display 220 can be positioned in front of the eyes ofthe user 210. The display 220 can present AR/VR/MR content to a user.The display 220 can comprise a head mounted display (HMD) that is wornon the head of the user.

In some embodiments, a speaker 240 is coupled to the frame 230 andpositioned adjacent the ear canal of the user (in some embodiments,another speaker, not shown, is positioned adjacent the other ear canalof the user to provide for stereo/shapeable sound control). The display220 can include an audio sensor (e.g., a microphone) 232 for detectingan audio stream from the environment and capture ambient sound. In someembodiments, one or more other audio sensors, not shown, are positionedto provide stereo sound reception. Stereo sound reception can be used todetermine the location of a sound source. The wearable system 200 canperform voice or speech recognition on the audio stream.

The wearable system 200 can include an outward-facing imaging system 464(shown in FIG. 4 ) which observes the world in the environment aroundthe user. The wearable system 200 can also include an inward-facingimaging system 462 (shown in FIG. 4 ) which can track the eye movementsof the user. The inward-facing imaging system may track either one eye’smovements or both eyes’ movements. The inward-facing imaging system 462may be attached to the frame 230 and may be in electrical communicationwith the processing modules 260 or 270, which may process imageinformation acquired by the inward-facing imaging system to determine,e.g., the pupil diameters or orientations of the eyes, eye movements oreye pose of the user 210. The inward-facing imaging system 462 mayinclude one or more cameras. For example, at least one camera may beused to image each eye. The images acquired by the cameras may be usedto determine pupil size or eye pose for each eye separately, therebyallowing presentation of image information to each eye to be dynamicallytailored to that eye.

As an example, the wearable system 200 can use the outward-facingimaging system 464 or the inward-facing imaging system 462 to acquireimages of a pose of the user. The images may be still images, frames ofa video, or a video.

The display 220 can be operatively coupled 250, such as by a wired leador wireless connectivity, to a local data processing module 260 whichmay be mounted in a variety of configurations, such as fixedly attachedto the frame 230, fixedly attached to a helmet or hat worn by the user,embedded in headphones, or otherwise removably attached to the user 210(e.g., in a backpack-style configuration, in a belt-coupling styleconfiguration).

The local processing and data module 260 may comprise a hardwareprocessor, as well as digital memory, such as non-volatile memory (e.g.,flash memory), both of which may be utilized to assist in theprocessing, caching, and storage of data. The data may include data a)captured from sensors (which may be, e.g., operatively coupled to theframe 230 or otherwise attached to the user 210), such as image capturedevices (e.g., cameras in the inward-facing imaging system or theoutward-facing imaging system), audio sensors (e.g., microphones),inertial measurement units (IMUs), accelerometers, compasses, globalpositioning system (GPS) units, radio devices, or gyroscopes; or b)acquired or processed using remote processing module 270 or remote datarepository 280, possibly for passage to the display 220 after suchprocessing or retrieval. The local processing and data module 260 may beoperatively coupled by communication links 262 or 264, such as via wiredor wireless communication links, to the remote processing module 270 orremote data repository 280 such that these remote modules are availableas resources to the local processing and data module 260. In addition,remote processing module 280 and remote data repository 280 may beoperatively coupled to each other.

In some embodiments, the remote processing module 270 may comprise oneor more processors configured to analyze and process data or imageinformation. In some embodiments, the remote data repository 280 maycomprise a digital data storage facility, which may be available throughthe internet or other networking configuration in a “cloud” resourceconfiguration. In some embodiments, all data is stored and allcomputations are performed in the local processing and data module,allowing fully autonomous use from a remote module.

Example Components of a Wearable System

FIG. 3 schematically illustrates example components of a wearablesystem. FIG. 3 shows a wearable system 200 which can include a display220 and a frame 230. A blown-up view 202 schematically illustratesvarious components of the wearable system 200. In certain implements,one or more of the components illustrated in FIG. 3 can be part of thedisplay 220. The various components alone or in combination can collecta variety of data (such as e.g., audio or visual data) associated withthe user of the wearable system 200 or the user’s environment. It shouldbe appreciated that other embodiments may have additional or fewercomponents depending on the application for which the wearable system isused. Nevertheless, FIG. 3 provides a basic idea of some of the variouscomponents and types of data that may be collected, analyzed, and storedthrough the wearable system.

FIG. 3 shows an example wearable system 200 which can include thedisplay 220. The display 220 can comprise a display lens 226 that may bemounted to a user’s head or a housing or frame 230, which corresponds tothe frame 230. The display lens 226 may comprise one or more transparentmirrors positioned by the housing 230 in front of the user’s eyes 302,304 and may be configured to bounce projected light 338 into the eyes302, 304 and facilitate beam shaping, while also allowing fortransmission of at least some light from the local environment. Thewavefront of the projected light beam 338 may be bent or focused tocoincide with a desired focal distance of the projected light. Asillustrated, two wide-field-of-view machine vision cameras 316 (alsoreferred to as world cameras) can be coupled to the housing 230 to imagethe environment around the user. These cameras 316 can be dual capturevisible light / non-visible (e.g., infrared) light cameras. The cameras316 may be part of the outward-facing imaging system 464 shown in FIG. 4. Image acquired by the world cameras 316 can be processed by the poseprocessor 336. For example, the pose processor 336 can implement one ormore object recognizers 708 (e.g., shown in FIG. 7 ) to identify a poseof a user or another person in the user’s environment or to identify aphysical object in the user’s environment.

With continued reference to FIG. 3 , a pair of scanned-lasershaped-wavefront (e.g., for depth) light projector modules with displaymirrors and optics configured to project light 338 into the eyes 302,304 are shown. The depicted view also shows two miniature infraredcameras 324 paired with light sources 326 (such as light emitting diodes″LED″s), which are configured to be able to track the eyes 302, 304 ofthe user to support rendering and user input. The light sources 326 mayemit light in the infrared (IR) portion of the optical spectrum, becausethe eyes 302, 304 are not sensitive to IR light and will not perceivethe light sources as shining into the user’s eyes, which would beuncomfortable. The cameras 324 may be part of the inward-facing imagingsystem 462 shown in FIG. 4 . The wearable system 200 can further featurea sensor assembly 339, which may comprise X, Y, and Z axis accelerometercapability as well as a magnetic compass and X, Y, and Z axis gyrocapability, preferably providing data at a relatively high frequency,such as 200 Hz. The sensor assembly 339 may be part of the IMU describedwith reference to FIG. 2 The depicted system 200 can also comprise ahead pose processor 336, such as an ASIC (application specificintegrated circuit), FPGA (field programmable gate array), or ARMprocessor (advanced reduced-instruction-set machine), which may beconfigured to calculate real or near-real time user head pose from widefield of view image information output from the capture devices 316. Thehead pose processor 336 can be a hardware processor and can beimplemented as part of the local processing and data module 260 shown inFIG. 2 .

The wearable system can also include one or more depth sensors 234. Thedepth sensor 234 can be configured to measure the distance between anobject in an environment to a wearable device. The depth sensor 234 mayinclude a laser scanner (e.g., a lidar), an ultrasonic depth sensor, ora depth sensing camera. In certain implementations, where the cameras316 have depth sensing ability, the cameras 316 may also be consideredas depth sensors 234.

Also shown is a processor 332 configured to execute digital or analogprocessing to derive pose from the gyro, compass, or accelerometer datafrom the sensor assembly 339. The processor 332 may be part of the localprocessing and data module 260 shown in FIG. 2 . The wearable system 200as shown in FIG. 3 can also include a position system such as, e.g., aGPS 337 (global positioning system) to assist with pose and positioninganalyses. In addition, the GPS may further provide remotely-based (e.g.,cloud-based) information about the user’s environment. This informationmay be used for recognizing objects or information in user’senvironment.

The wearable system may combine data acquired by the GPS 337 and aremote computing system (such as, e.g., the remote processing module270, another user’s ARD, etc.) which can provide more information aboutthe user’s environment. As one example, the wearable system candetermine the user’s location based on GPS data and retrieve a world map(e.g., by communicating with a remote processing module 270) includingvirtual objects associated with the user’s location. As another example,the wearable system 200 can monitor the environment using the worldcameras 316 (which may be part of the outward-facing imaging system 464shown in FIG. 4 ). Based on the images acquired by the world cameras316, the wearable system 200 can detect objects in the environment. Thewearable system can further use data acquired by the GPS 337 tointerpret the characters.

The wearable system 200 may also comprise a rendering engine 334 whichcan be configured to provide rendering information that is local to theuser to facilitate operation of the scanners and imaging into the eyesof the user, for the user’s view of the world. The rendering engine 334may be implemented by a hardware processor (such as, e.g., a centralprocessing unit or a graphics processing unit). In some embodiments, therendering engine is part of the local processing and data module 260.The rendering engine 334 may comprise the light-field render controller618 described with reference to FIGS. 6 and 7 . The rendering engine 334can be communicatively coupled (e.g., via wired or wireless links) toother components of the wearable system 200. For example, the renderingengine 334, can be coupled to the eye cameras 324 via communication link274, and be coupled to a projecting subsystem 318 (which can projectlight into user’s eyes 302, 304 via a scanned laser arrangement in amanner similar to a retinal scanning display) via the communication link272. The rendering engine 334 can also be in communication with otherprocessing units such as, e.g., the sensor pose processor 332 and theimage pose processor 336 via links 276 and 294 respectively.

The cameras 324 (e.g., mini infrared cameras) may be utilized to trackthe eye pose to support rendering and user input. Some example eye posesmay include where the user is looking or at what depth he or she isfocusing (which may be estimated with eye vergence). The cameras 324 andthe infrared light sources 326 can be used to provide data to for themultiple exposure time eye-tracking techniques described herein. The GPS337, gyros, compass, and accelerometers 339 may be utilized to providecoarse or fast pose estimates. One or more of the cameras 316 canacquire images and pose, which in conjunction with data from anassociated cloud computing resource, may be utilized to map the localenvironment and share user views with others.

The example components depicted in FIG. 3 are for illustration purposesonly. Multiple sensors and other functional modules are shown togetherfor ease of illustration and description. Some embodiments may includeonly one or a subset of these sensors or modules. Further, the locationsof these components are not limited to the positions depicted in FIG. 3. Some components may be mounted to or housed within other components,such as a belt-mounted component, a hand-held component, or a helmetcomponent. As one example, the image pose processor 336, sensor poseprocessor 332, and rendering engine 334 may be positioned in a beltpackand configured to communicate with other components of the wearablesystem via wireless communication, such as ultra-wideband, Wi-Fi,Bluetooth, etc., or via wired communication. The depicted housing 230preferably is head-mountable and wearable by the user. However, somecomponents of the wearable system 200 may be worn to other portions ofthe user’s body. For example, the speaker 240 may be inserted into theears of a user to provide sound to the user.

Regarding the projection of light 338 into the eyes 302, 304 of theuser, in some embodiment, the cameras 324 may be utilized to measurewhere the centers of a user’s eyes are geometrically verged to, which,in general, coincides with a position of focus, or “depth of focus”, ofthe eyes. A 3-dimensional surface of all points the eyes verge to can bereferred to as the “horopter”. The focal distance may take on a finitenumber of depths, or may be infinitely varying. Light projected from thevergence distance appears to be focused to the subject eye 302, 304,while light in front of or behind the vergence distance is blurred.Examples of wearable devices and other display systems of the presentdisclosure are also described in U.S. Patent Publication No.2016/0270656, which is incorporated by reference herein in its entirety.

The human visual system is complicated and providing a realisticperception of depth is challenging. Viewers of an object may perceivethe object as being three-dimensional due to a combination of vergenceand accommodation. Vergence movements (e.g., rolling movements of thepupils toward or away from each other to converge the lines of sight ofthe eyes to fixate upon an object) of the two eyes relative to eachother are closely associated with focusing (or “accommodation”) of thelenses of the eyes. Under normal conditions, changing the focus of thelenses of the eyes, or accommodating the eyes, to change focus from oneobject to another object at a different distance will automaticallycause a matching change in vergence to the same distance, under arelationship known as the “accommodation-vergence reflex.” Likewise, achange in vergence will trigger a matching change in accommodation,under normal conditions. Display systems that provide a better matchbetween accommodation and vergence may form more realistic andcomfortable simulations of three-dimensional imagery.

Further spatially coherent light with a beam diameter of less than about0.7 millimeters can be correctly resolved by the human eye regardless ofwhere the eye focuses. Thus, to create an illusion of proper focaldepth, the eye vergence may be tracked with the cameras 324, and therendering engine 334 and projection subsystem 318 may be utilized torender all objects on or close to the horopter in focus, and all otherobjects at varying degrees of defocus (e.g., using intentionally-createdblurring). Preferably, the system 220 renders to the user at a framerate of about 60 frames per second or greater. As described above,preferably, the cameras 324 may be utilized for eye tracking, andsoftware may be configured to pick up not only vergence geometry butalso focus location cues to serve as user inputs. Preferably, such adisplay system is configured with brightness and contrast suitable forday or night use.

In some embodiments, the display system preferably has latency of lessthan about 20 milliseconds for visual object alignment, less than about0.1 degree of angular alignment, and about 1 arc minute of resolution,which, without being limited by theory, is believed to be approximatelythe limit of the human eye. The display system 220 may be integratedwith a localization system, which may involve GPS elements, opticaltracking, compass, accelerometers, or other data sources, to assist withposition and pose determination; localization information may beutilized to facilitate accurate rendering in the user’s view of thepertinent world (e.g., such information would facilitate the glasses toknow where they are with respect to the real world).

In some embodiments, the wearable system 200 is configured to displayone or more virtual images based on the accommodation of the user’seyes. Unlike prior 3D display approaches that force the user to focuswhere the images are being projected, in some embodiments, the wearablesystem is configured to automatically vary the focus of projectedvirtual content to allow for a more comfortable viewing of one or moreimages presented to the user. For example, if the user’s eyes have acurrent focus of 1 m, the image may be projected to coincide with theuser’s focus. If the user shifts focus to 3 m, the image is projected tocoincide with the new focus. Thus, rather than forcing the user to apredetermined focus, the wearable system 200 of some embodiments allowsthe user’s eye to a function in a more natural manner.

Such a wearable system 200 may eliminate or reduce the incidences of eyestrain, headaches, and other physiological symptoms typically observedwith respect to virtual reality devices. To achieve this, variousembodiments of the wearable system 200 are configured to project virtualimages at varying focal distances, through one or more variable focuselements (VFEs). In one or more embodiments, 3D perception may beachieved through a multi-plane focus system that projects images atfixed focal planes away from the user. Other embodiments employ variableplane focus, wherein the focal plane is moved back and forth in thez-direction to coincide with the user’s present state of focus.

In both the multi-plane focus systems and variable plane focus systems,wearable system 200 may employ eye tracking to determine a vergence ofthe user’s eyes, determine the user’s current focus, and project thevirtual image at the determined focus. In other embodiments, wearablesystem 200 comprises a light modulator that variably projects, through afiber scanner, or other light generating source, light beams of varyingfocus in a raster pattern across the retina. Thus, the ability of thedisplay of the wearable system 200 to project images at varying focaldistances not only eases accommodation for the user to view objects in3D, but may also be used to compensate for user ocular anomalies, asfurther described in U.S. Patent Publication No. 2016/0270656, which isincorporated by reference herein in its entirety. In some otherembodiments, a spatial light modulator may project the images to theuser through various optical components. For example, as describedfurther below, the spatial light modulator may project the images ontoone or more waveguides, which then transmit the images to the user.

Waveguide Stack Assembly

FIG. 4 illustrates an example of a waveguide stack for outputting imageinformation to a user. A wearable system 400 includes a stack ofwaveguides, or stacked waveguide assembly 480 that may be utilized toprovide three-dimensional perception to the eye/brain using a pluralityof waveguides 432 b, 434 b, 436 b, 438 b, 440 b. In some embodiments,the wearable system 400 may correspond to wearable system 200 of FIG. 2, with FIG. 4 schematically showing some parts of that wearable system200 in greater detail. For example, in some embodiments, the waveguideassembly 480 may be integrated into the display 220 of FIG. 2 .

With continued reference to FIG. 4 , the waveguide assembly 480 may alsoinclude a plurality of features 458, 456, 454, 452 between thewaveguides. In some embodiments, the features 458, 456, 454, 452 may belenses. In other embodiments, the features 458, 456, 454, 452 may not belenses. Rather, they may simply be spacers (e.g., cladding layers orstructures for forming air gaps).

The waveguides 432 b, 434 b, 436 b, 438 b, 440 b or the plurality oflenses 458, 456, 454, 452 may be configured to send image information tothe eye with various levels of wavefront curvature or light raydivergence. Each waveguide level may be associated with a particulardepth plane and may be configured to output image informationcorresponding to that depth plane. Image injection devices 420, 422,424, 426, 428 may be utilized to inject image information into thewaveguides 440 b, 438 b, 436 b, 434 b, 432 b, each of which may beconfigured to distribute incoming light across each respectivewaveguide, for output toward the eye 410. Light exits an output surfaceof the image injection devices 420, 422, 424, 426, 428 and is injectedinto a corresponding input edge of the waveguides 440 b, 438 b, 436 b,434 b, 432 b. In some embodiments, a single beam of light (e.g., acollimated beam) may be injected into each waveguide to output an entirefield of cloned collimated beams that are directed toward the eye 410 atparticular angles (and amounts of divergence) corresponding to the depthplane associated with a particular waveguide.

In some embodiments, the image injection devices 420, 422, 424, 426, 428are discrete displays that each produce image information for injectioninto a corresponding waveguide 440 b, 438 b, 436 b, 434 b, 432 b,respectively. In some other embodiments, the image injection devices420, 422, 424, 426, 428 are the output ends of a single multiplexeddisplay which may, e.g., pipe image information via one or more opticalconduits (such as fiber optic cables) to each of the image injectiondevices 420, 422, 424, 426, 428.

A controller 460 controls the operation of the stacked waveguideassembly 480 and the image injection devices 420, 422, 424, 426, 428.The controller 460 includes programming (e.g., instructions in anon-transitory computer-readable medium) that regulates the timing andprovision of image information to the waveguides 440 b, 438 b, 436 b,434 b, 432 b. In some embodiments, the controller 460 may be a singleintegral device, or a distributed system connected by wired or wirelesscommunication channels. The controller 460 may be part of the processingmodules 260 or 270 (illustrated in FIG. 2 ) in some embodiments.

The waveguides 440 b, 438 b, 436 b, 434 b, 432 b may be configured topropagate light within each respective waveguide by total internalreflection (TIR). The waveguides 440 b, 438 b, 436 b, 434 b, 432 b mayeach be planar or have another shape (e.g., curved), with major top andbottom surfaces and edges extending between those major top and bottomsurfaces. In the illustrated configuration, the waveguides 440 b, 438 b,436 b, 434 b, 432 b may each include light extracting optical elements440 a, 438 a, 436 a, 434 a, 432 a that are configured to extract lightout of a waveguide by redirecting the light, propagating within eachrespective waveguide, out of the waveguide to output image informationto the eye 410. Extracted light may also be referred to as outcoupledlight, and light extracting optical elements may also be referred to asoutcoupling optical elements. An extracted beam of light is outputted bythe waveguide at locations at which the light propagating in thewaveguide strikes a light redirecting element. The light extractingoptical elements (440 a, 438 a, 436 a, 434 a, 432 a) may, for example,be reflective or diffractive optical features. While illustrateddisposed at the bottom major surfaces of the waveguides 440 b, 438 b,436 b, 434 b, 432 b for ease of description and drawing clarity, in someembodiments, the light extracting optical elements 440 a, 438 a, 436 a,434 a, 432 a may be disposed at the top or bottom major surfaces, or maybe disposed directly in the volume of the waveguides 440 b, 438 b, 436b, 434 b, 432 b. In some embodiments, the light extracting opticalelements 440 a, 438 a, 436 a, 434 a, 432 a may be formed in a layer ofmaterial that is attached to a transparent substrate to form thewaveguides 440 b, 438 b, 436 b, 434 b, 432 b. In some other embodiments,the waveguides 440 b, 438 b, 436 b, 434 b, 432 b may be a monolithicpiece of material and the light extracting optical elements 440 a, 438a, 436 a, 434 a, 432 a may be formed on a surface or in the interior ofthat piece of material.

With continued reference to FIG. 4 , as discussed herein, each waveguide440 b, 438 b, 436 b, 434 b, 432 b is configured to output light to forman image corresponding to a particular depth plane. For example, thewaveguide 432 b nearest the eye may be configured to deliver collimatedlight, as injected into such waveguide 432 b, to the eye 410. Thecollimated light may be representative of the optical infinity focalplane. The next waveguide up 434 b may be configured to send outcollimated light which passes through the first lens 452 (e.g., anegative lens) before it can reach the eye 410. First lens 452 may beconfigured to create a slight convex wavefront curvature so that theeye/brain interprets light coming from that next waveguide up 434 b ascoming from a first focal plane closer inward toward the eye 410 fromoptical infinity. Similarly, the third up waveguide 436 b passes itsoutput light through both the first lens 452 and second lens 454 beforereaching the eye 410. The combined optical power of the first and secondlenses 452 and 454 may be configured to create another incrementalamount of wavefront curvature so that the eye/brain interprets lightcoming from the third waveguide 436 b as coming from a second focalplane that is even closer inward toward the person from optical infinitythan was light from the next waveguide up 434 b.

The other waveguide layers (e.g., waveguides 438 b, 440 b) and lenses(e.g., lenses 456, 458) are similarly configured, with the highestwaveguide 440 b in the stack sending its output through all of thelenses between it and the eye for an aggregate focal powerrepresentative of the closest focal plane to the person. To compensatefor the stack of lenses 458, 456, 454, 452 when viewing/interpretinglight coming from the world 470 on the other side of the stackedwaveguide assembly 480, a compensating lens layer 430 may be disposed atthe top of the stack to compensate for the aggregate power of the lensstack 458, 456, 454, 452 below. (Compensating lens layer 430 and thestacked waveguide assembly 480 as a whole may be configured such thatlight coming from the world 470 is conveyed to the eye 410 atsubstantially the same level of divergence (or collimation) as the lighthad when it was initially received by the stacked waveguide assembly480.) Such a configuration provides as many perceived focal planes asthere are available waveguide/lens pairings. Both the light extractingoptical elements of the waveguides and the focusing aspects of thelenses may be static (e.g., not dynamic or electro-active). In somealternative embodiments, either or both may be dynamic usingelectro-active features.

With continued reference to FIG. 4 , the light extracting opticalelements 440 a, 438 a, 436 a, 434 a, 432 a may be configured to bothredirect light out of their respective waveguides and to output thislight with the appropriate amount of divergence or collimation for aparticular depth plane associated with the waveguide. As a result,waveguides having different associated depth planes may have differentconfigurations of light extracting optical elements, which output lightwith a different amount of divergence depending on the associated depthplane. In some embodiments, as discussed herein, the light extractingoptical elements 440 a, 438 a, 436 a, 434 a, 432 a may be volumetric orsurface features, which may be configured to output light at specificangles. For example, the light extracting optical elements 440 a, 438 a,436 a, 434 a, 432 a may be volume holograms, surface holograms, and/ordiffraction gratings. Light extracting optical elements, such asdiffraction gratings, are described in U.S. Patent Publication No.2015/0178939, published Jun. 25, 2015, which is incorporated byreference herein in its entirety.

In some embodiments, the light extracting optical elements 440 a, 438 a,436 a, 434 a, 432 a are diffractive features that form a diffractionpattern, or “diffractive optical element” (also referred to herein as a“DOE”). Preferably, the DOE has a relatively low diffraction efficiencyso that only a portion of the light of the beam is deflected away towardthe eye 410 with each intersection of the DOE, while the rest continuesto move through a waveguide via total internal reflection. The lightcarrying the image information can thus be divided into a number ofrelated exit beams that exit the waveguide at a multiplicity oflocations and the result is a fairly uniform pattern of exit emissiontoward the eye 304 for this particular collimated beam bouncing aroundwithin a waveguide.

In some embodiments, one or more DOEs may be switchable between “on”state in which they actively diffract, and “off” state in which they donot significantly diffract. For instance, a switchable DOE may comprisea layer of polymer dispersed liquid crystal, in which microdropletscomprise a diffraction pattern in a host medium, and the refractiveindex of the microdroplets can be switched to substantially match therefractive index of the host material (in which case the pattern doesnot appreciably diffract incident light) or the microdroplet can beswitched to an index that does not match that of the host medium (inwhich case the pattern actively diffracts incident light).

In some embodiments, the number and distribution of depth planes ordepth of field may be varied dynamically based on the pupil sizes ororientations of the eyes of the viewer. Depth of field may changeinversely with a viewer’s pupil size. As a result, as the sizes of thepupils of the viewer’s eyes decrease, the depth of field increases suchthat one plane that is not discernible because the location of thatplane is beyond the depth of focus of the eye may become discernible andappear more in focus with reduction of pupil size and commensurate withthe increase in depth of field. Likewise, the number of spaced apartdepth planes used to present different images to the viewer may bedecreased with the decreased pupil size. For example, a viewer may notbe able to clearly perceive the details of both a first depth plane anda second depth plane at one pupil size without adjusting theaccommodation of the eye away from one depth plane and to the otherdepth plane. These two depth planes may, however, be sufficiently infocus at the same time to the user at another pupil size withoutchanging accommodation.

In some embodiments, the display system may vary the number ofwaveguides receiving image information based upon determinations ofpupil size or orientation, or upon receiving electrical signalsindicative of particular pupil size or orientation. For example, if theuser’s eyes are unable to distinguish between two depth planesassociated with two waveguides, then the controller 460 (which may be anembodiment of the local processing and data module 260) can beconfigured or programmed to cease providing image information to one ofthese waveguides. Advantageously, this may reduce the processing burdenon the system, thereby increasing the responsiveness of the system. Inembodiments in which the DOEs for a waveguide are switchable between theon and off states, the DOEs may be switched to the off state when thewaveguide does receive image information.

In some embodiments, it may be desirable to have an exit beam meet thecondition of having a diameter that is less than the diameter of the eyeof a viewer. However, meeting this condition may be challenging in viewof the variability in size of the viewer’s pupils. In some embodiments,this condition is met over a wide range of pupil sizes by varying thesize of the exit beam in response to determinations of the size of theviewer’s pupil. For example, as the pupil size decreases, the size ofthe exit beam may also decrease. In some embodiments, the exit beam sizemay be varied using a variable aperture.

The wearable system 400 can include an outward-facing imaging system 464(e.g., a digital camera) that images a portion of the world 470. Thisportion of the world 470 may be referred to as the field of view (FOV)of a world camera and the imaging system 464 is sometimes referred to asan FOV camera. The FOV of the world camera may or may not be the same asthe FOV of a viewer 210 which encompasses a portion of the world 470 theviewer 210 perceives at a given time. For example, in some situations,the FOV of the world camera may be larger than the viewer 210 of theviewer 210 of the wearable system 400. The entire region available forviewing or imaging by a viewer may be referred to as the field of regard(FOR). The FOR may include 4π steradians of solid angle surrounding thewearable system 400 because the wearer can move his body, head, or eyesto perceive substantially any direction in space. In other contexts, thewearer’s movements may be more constricted, and accordingly the wearer’sFOR may subtend a smaller solid angle. Images obtained from theoutward-facing imaging system 464 can be used to track gestures made bythe user (e.g., hand or finger gestures), detect objects in the world470 in front of the user, and so forth.

The wearable system 400 can include an audio sensor 232, e.g., amicrophone, to capture ambient sound. As described above, in someembodiments, one or more other audio sensors can be positioned toprovide stereo sound reception useful to the determination of locationof a speech source. The audio sensor 232 can comprise a directionalmicrophone, as another example, which can also provide such usefuldirectional information as to where the audio source is located. Thewearable system 400 can use information from both the outward-facingimaging system 464 and the audio sensor 230 in locating a source ofspeech, or to determine an active speaker at a particular moment intime, etc. For example, the wearable system 400 can use the voicerecognition alone or in combination with a reflected image of thespeaker (e.g., as seen in a mirror) to determine the identity of thespeaker. As another example, the wearable system 400 can determine aposition of the speaker in an environment based on sound acquired fromdirectional microphones. The wearable system 400 can parse the soundcoming from the speaker’s position with speech recognition algorithms todetermine the content of the speech and use voice recognition techniquesto determine the identity (e.g., name or other demographic information)of the speaker.

The wearable system 400 can also include an inward-facing imaging system466 (comprising, e.g., a digital camera), which observes the movementsof the user, such as the eye movements (e.g., for eye-tracking) and thefacial movements. The inward-facing imaging system 466 may be used tocapture images of the eye 410 to determine the size and/or orientationof the pupil of the eye 304. The inward-facing imaging system 466 can beused to obtain images for use in determining the direction the user islooking (e.g., eye pose) or for biometric identification of the user(e.g., via iris identification). The inward-facing imaging system 426can be used to provide input images and information for the multipleexposure time eye-tracking techniques described herein. In someembodiments, at least one camera may be utilized for each eye, toseparately determine the pupil size or eye pose of each eyeindependently, thereby allowing the presentation of image information toeach eye to be dynamically tailored to that eye. In some otherembodiments, the pupil diameter or orientation of only a single eye 410(e.g., using only a single camera per pair of eyes) is determined andassumed to be similar for both eyes of the user. The images obtained bythe inward-facing imaging system 466 may be analyzed to determine theuser’s eye pose or mood, which can be used by the wearable system 400 todecide which audio or visual content should be presented to the user.The wearable system 400 may also determine head pose (e.g., headposition or head orientation) using sensors such as IMUs,accelerometers, gyroscopes, etc. The inward-facing imaging system 426can comprise the cameras 324 and light sources 326 (e.g., IR LEDs)described with reference to FIG. 3 .

The wearable system 400 can include a user input device 466 by which theuser can input commands to the controller 460 to interact with thewearable system 400. For example, the user input device 466 can includea trackpad, a touchscreen, a joystick, a multiple degree-of-freedom(DOF) controller, a capacitive sensing device, a game controller, akeyboard, a mouse, a directional pad (D-pad), a wand, a haptic device, atotem (e.g., functioning as a virtual user input device), and so forth.A multi-DOF controller can sense user input in some or all possibletranslations (e.g., left/right, forward/backward, or up/down) orrotations (e.g., yaw, pitch, or roll) of the controller. A multi-DOFcontroller which supports the translation movements may be referred toas a 3DOF while a multi-DOF controller which supports the translationsand rotations may be referred to as 6DOF. In some cases, the user mayuse a finger (e.g., a thumb) to press or swipe on a touch-sensitiveinput device to provide input to the wearable system 400 (e.g., toprovide user input to a user interface provided by the wearable system400). The user input device 466 may be held by the user’s hand duringthe use of the wearable system 400. The user input device 466 can be inwired or wireless communication with the wearable system 400.

Example of an Eye Image

FIG. 5 illustrates an image of an eye 500 with eyelids 504, sclera 508(the “white” of the eye), iris 512, and pupil 516. Curve 516 a shows thepupillary boundary between the pupil 516 and the iris 512, and curve 512a shows the limbic boundary between the iris 512 and the sclera 508. Theeyelids 504 include an upper eyelid 504 a and a lower eyelid 504 b. Theeye 500 is illustrated in a natural resting pose (e.g., in which theuser’s face and gaze are both oriented as they would be toward a distantobject directly ahead of the user). The natural resting pose of the eye500 can be indicated by a natural resting direction 520, which is adirection orthogonal to the surface of the eye 500 when in the naturalresting pose (e.g., directly out of the plane for the eye 500 shown inFIG. 5 ) and in this example, centered within the pupil 516.

As the eye 500 moves to look toward different objects, the eye pose willchange relative to the natural resting direction 520. The current eyepose can be determined with reference to an eye pose direction 524,which is a direction orthogonal to the surface of the eye (and centeredin within the pupil 516) but oriented toward the object at which the eyeis currently directed. With reference to an example coordinate systemshown in FIG. 5A, the pose of the eye 500 can be expressed as twoangular parameters indicating an azimuthal deflection and a zenithaldeflection of the eye pose direction 524 of the eye, both relative tothe natural resting direction 520 of the eye. For purposes ofillustration, these angular parameters can be represented as θ(azimuthal deflection, determined from a fiducial azimuth) and ϕ(zenithal deflection, sometimes also referred to as a polar deflection).In some implementations, angular roll of the eye around the eye posedirection 524 can be included in the determination of eye pose, andangular roll can be included in the eye-tracking. In otherimplementations, other techniques for determining the eye pose can beused, for example, a pitch, yaw, and optionally roll system. Thus, theeye pose can be provided as a 2DOF or a 3DOF orientation.

The light sources 326 can illuminate the eye 500 (e.g., in the IR), andreflections of the light sources from the eye (typically off of thecornea) are referred to as glints. FIG. 5 schematically shows an examplewhere there are four glints 550. The positions, number, brightnesses,etc. of the glints 550 can depend on the position and number of thelight sources 326, the pose of the eye, and so forth. As will be furtherdescribed below, an eye-tracking camera 324 can obtain eye images, and aprocessor can analyze the eye images to determine positions andmovements of the glints for eye-tracking. In some embodiments, multipleeye images with different exposure times or different frame rates can beused to provide high accuracy eye tracking.

An eye image can be obtained from a video using any appropriate process,for example, using a video processing algorithm that can extract animage from one or more sequential frames (or non-sequential frames). Theinward-facing imaging system 426 of FIG. 4 or the camera 324 and lightsource 326 of FIG. 3 can be utilized to provide the video or image(s) ofone or both of the eyes. The pose of the eye can be determined from theeye image using a variety of eye-tracking techniques, for example, themultiple exposure time techniques for accurate corneal glint detectionthat are described herein. For example, an eye pose can be determined byconsidering the lensing effects of the cornea on light sources that areprovided. Any suitable eye tracking technique can be used fordetermining eye pose in the eyelid shape estimation techniques describedherein.

Example of an Eye Tracking System

FIG. 6 illustrates a schematic diagram of a wearable system 600 thatincludes an eye tracking system 601. The wearable system 600 may be anembodiment of the wearable systems 200 and 400 described with referenceto FIGS. 2 to 4 . The wearable system 600 may, in at least someembodiments, include components located in a head-mounted unit 602 andcomponents located in a non-head-mounted unit 604. Non-head mounted unit604 may be, as examples, a belt-mounted component, a hand-heldcomponent, a component in a backpack, a remote component, etc.Incorporating some of the components of the wearable system 600 innon-head-mounted unit 604 may help to reduce the size, weight,complexity, and cost of the head-mounted unit 602. In someimplementations, some or all of the functionality described as beingperformed by one or more components of head-mounted unit 602 and/ornon-head mounted unit 604 may be provided by way of one or morecomponents included elsewhere in the wearable system 600. For example,some or all of the functionality described below in association with aCPU 612 of head-mounted unit 602 may be provided by way of a CPU 616 ofnon-head mounted unit 604, and vice versa. In some examples, some or allof such functionality may be provided by way of peripheral devices ofwearable system 600. Furthermore, in some implementations, some or allof such functionality may be provided by way of one or more cloudcomputing devices or other remotely-located computing devices in amanner similar to that which has been described above with reference toFIG. 2 .

As shown in FIG. 6 , wearable system 600 can include an eye trackingsystem 601 including a camera 324 that captures images of a user’s eye610. If desired, the eye tracking system may also include light sources326 a and 326 b (such as light emitting diodes ″LED″s). The lightsources 326 a and 326 b may generate glints (e.g., reflections off ofthe user’s eyes that appear in images of the eye captured by camera324). Schematic examples of glints 550 are shown in FIG. 5 . Thepositions of the light sources 326 a and 326 b relative to the camera324 may be known and, as a consequence, the positions of the glintswithin images captured by camera 324 can be used in tracking the user’seyes (as will be described in more detail below). In at least oneembodiment, there may be one light source 326 and one camera 324associated with a single one of the user’s eyes 610. In anotherembodiment, there may be one light source 326 and one camera 324associated with each of a user’s eyes. 610. In yet other embodiments,there may be one or more cameras 324 and one or more light sources 326associated with one or each of a user’s eyes 610. As a specific example,there may be two light sources 326 a and 326 b and one or more cameras324 associated with each of a user’s eyes 610. As another example, theremay be three or more light sources such as light sources 326 a and 326 band one or more cameras 324 associated with each of a user’s eyes 610.

Eye tracking module 614 may receive images from eye tracking camera(s)324 and may analyze the images to extract various pieces of information.As described herein, the images from the eye tracking camera(s) mayinclude shorter exposure (glint) images and longer exposure images. Asexamples, the eye tracking module 614 may detect the user’s eye poses, athree-dimensional position of the user’s eye relative to the eyetracking camera 324 (and to the head-mounted unit 602), the directionone or both of the user’s eyes 610 are focused on, the user’s vergencedepth (e.g., the depth from the user at which the user is focusing on),the positions of the user’s pupils, the positions of the user’s corneaand corneal sphere, the center of rotation of each of the user’s eyes,or the center of perspective of each of the user’s eyes. As shown inFIG. 6 , the eye tracking module 614 may be a software moduleimplemented using a CPU 612 in a head-mounted unit 602.

Data from eye tracking module 614 may be provided to other components inthe wearable system. As example, such data may be transmitted tocomponents in a non-head-mounted unit 604 such as CPU 616 includingsoftware modules for a light-field render controller 618 and aregistration observer 620.

As described further herein, in some implementations of the multipleexposure time eye tracking technology, the functionality may beperformed differently than shown in FIG. 6 (or FIG. 7 ), which areintended to be illustrative and not limiting. For example, in someimplementations, the shorter exposure glint images can be processed bythe CPU 612 in the head-mounted unit 602 (which may be disposed in thecamera 324) and the longer exposure images can be processed by the CPU616 (or GPU 621) in the non-head mounted unit 604 (e.g., in a beltpack).In some such implementations, some of the eye tracking functionalityperformed by the eye tracking module 614 may be performed by a processor(e.g., the CPU 616 or GPU 621) in the non-head mounted unit 604 (e.g.,the beltpack). This may be advantageous because some of the eye trackingfunctionality may be CPU-intensive and may, in some cases, be performedmore efficiently or rapidly by a more powerful processor disposed in thenon-head mounted unit 604.

Render controller 618 may use information from eye tracking module 614to adjust images displayed to the user by render engine 622 (e.g., arender engine that may be a software module in GPU 620 and that mayprovide images to the display 220). As an example, the render controller618 may adjust images displayed to the user based on the user’s centerof rotation or center of perspective. In particular, the rendercontroller 618 may use information on the user’s center of perspectiveto simulate a render camera (e.g., to simulate collecting images fromthe user’s perspective) and may adjust images displayed to the userbased on the simulated render camera. Further details discussing thecreation, adjustment, and use of render cameras in rendering processesare provided in U.S. Patent Application No. 15/274,823, published asU.S. Patent Application Publication No. 2017/0091996, entitled “METHODSAND SYSTEMS FOR DETECTING AND COMBINING STRUCTURAL FEATURES IN 3DRECONSTRUCTION,” which is expressly incorporated by reference herein inits entirety.

In some examples, one or more modules (or components) of the system 600(e.g., light-field render controller 618, render engine 620, etc.) maydetermine the position and orientation of the render camera withinrender space based on the position and orientation of the user’s headand eyes (e.g., as determined based on head pose and eye tracking data,respectively). For example, the system 600 may effectively map theposition and orientation of the user’s head and eyes to particularlocations and angular positions within a 3D virtual environment, placeand orient render cameras at the particular locations and angularpositions within the 3D virtual environment, and render virtual contentfor the user as it would be captured by the render camera. Furtherdetails discussing real world to virtual world mapping processes areprovided in U.S. Patent Application No. 15/296,869, published as U.S.Patent Application Publication No. 2017/0109936, entitled “SELECTINGVIRTUAL OBJECTS IN A THREE-DIMENSIONAL SPACE,” which is expresslyincorporated by reference herein in its entirety. As an example, therender controller 618 may adjust the depths at which images aredisplayed by selecting which depth plane (or depth planes) are utilizedat any given time to display the images. In some implementations, such adepth plane switch may be carried out through an adjustment of one ormore intrinsic render camera parameters.

Registration observer 620 may use information from the eye trackingmodule 614 to identify whether the head-mounted unit 602 is properlypositioned on a user’s head. As an example, the eye tracking module 614may provide eye location information, such as the positions of thecenters of rotation of the user’s eyes, indicative of thethree-dimensional position of the user’s eyes relative to camera 324 andhead-mounted unit 602 and the eye tracking module 614 may use thelocation information to determine if display 220 is properly aligned inthe user’s field of view, or if the head-mounted unit 602 (or headset)has slipped or is otherwise misaligned with the user’s eyes. Asexamples, the registration observer 620 may be able to determine if thehead-mounted unit 602 has slipped down the user’s nose bridge, thusmoving display 220 away and down from the user’s eyes (which may beundesirable), if the head-mounted unit 602 has been moved up the user’snose bridge, thus moving display 220 closer and up from the user’s eyes,if the head-mounted unit 602 has been shifted left or right relative theuser’s nose bridge, if the head-mounted unit 602 has been lifted abovethe user’s nose bridge, or if the head-mounted unit 602 has been movedin these or other ways away from a desired position or range ofpositions. In general, registration observer 620 may be able todetermine if head-mounted unit 602, in general, and displays 220, inparticular, are properly positioned in front of the user’s eyes. Inother words, the registration observer 620 may determine if a leftdisplay in display system 220 is appropriately aligned with the user’sleft eye and a right display in display system 220 is appropriatelyaligned with the user’s right eye. The registration observer 620 maydetermine if the head-mounted unit 602 is properly positioned bydetermining if the head-mounted unit 602 is positioned and orientedwithin a desired range of positions and/or orientations relative to theuser’s eyes. Example registration observation and feedback techniques,which may be utilized by the registration observer 620, are described inU.S. Patent Application No. 15/717,747, filed Sep. 27, 2017, publishedas U.S. Patent Application Publication No. 2018/0096503, entitled“PERIOCULAR TEST FOR MIXED REALITY CALIBRATION” and U.S. PatentApplication No. 16/251,017, filed Jan. 17, 2019, published as U.S.Patent Application Publication No. 2019/0222830, entitled “DISPLAYSYSTEMS AND METHODS FOR DETERMINING REGISTRATION BETWEEN A DISPLAY AND AUSER’S EYES,” both of which are incorporated by reference herein intheir entireties.

The render controller 618 can receive eye tracking information from theeye tracking module 614 and may provide outputs to the render engine622, which can generate images to be displayed for viewing by a user ofthe wearable system 600. As examples, the render controller 618 mayreceive a vergence depth, left and right eye centers of rotation (and/orcenters of perspective), and other eye data such as blink data, saccadedata, etc. Vergence depth information and other eye data and, based onsuch data, can cause the render engine 622 to convey content to a userwith a particular depth plane (e.g., at a particular accommodation orfocal distance). As discussed in connection with FIG. 4 , the wearablesystem may include a plurality of discrete depth planes formed by aplurality of waveguides, each conveying image information with a varyinglevel of wavefront curvature. In some embodiments, a wearable system mayinclude one or more variable depth planes, such as an optical elementthat conveys image information with a level of wavefront curvature thatvaries over time. The render engine 622 can convey content to a user ata selected depth (e.g., cause the render engine 622 to direct thedisplay 220 to switch depth planes), based in part of the user’svergence depth.

The render engine 622 can generate content by simulating cameras at thepositions of the user’s left and right eyes and generating content basedon the perspectives of the simulated cameras. As discussed above, therender camera is a simulated camera for use in rendering virtual imagecontent possibly from a database of objects in a virtual world. Theobjects may have locations and orientations relative to the user orwearer and possibly relative to real objects in the environmentsurrounding the user or wearer. The render camera may be included in arender engine to render virtual images based on the database of virtualobjects to be presented to the eye. The virtual images may be renderedas if taken from the perspective the user or wearer. For example, thevirtual images may be rendered as if captured by a camera (correspondingto the “render camera”) having an aperture, lens, and detector viewingthe objects in the virtual world. The virtual images are taken from theperspective of such a camera having a position of the “render camera.”For example, the virtual images may be rendered as if captured from theperspective of a camera having a specific location with respect to theuser’s or wearer’s eye so as to provide images that appear to be fromthe perspective of the user or wearer. In some implementations, theimages are rendered as if captured from the perspective of a camerahaving an aperture at a specific location with respect to the user’s orwearer’s eye (such as the center of perspective or center of rotation asdiscussed herein, or elsewhere).

Example of an Eye Tracking Module

A block diagram of an example eye tracking module 614 is shown in FIG. 7. As shown in FIG. 7 , the eye tracking module 614 may include a varietyof different submodules, may provide a variety of different outputs, andmay utilize a variety of available data in tracking the user’s eyes. Asexamples, eye tracking module 614 may utilize available data includingeye tracking extrinsics and intrinsics, such as the geometricarrangements of the eye tracking camera 324 relative to the lightsources 326 and the head-mounted-unit 602; assumed eye dimensions 704such as a typical distance of approximately 4.7 mm between a user’scenter of cornea curvature and the average center of rotation of theuser’s eye or typical distances between a user’s center of rotation andcenter of perspective; and per-user calibration data 706 such as aparticular user’s interpupillary distance. Additional examples ofextrinsics, intrinsics, and other information that may be employed bythe eye tracking module 614 are described in U.S. Patent Application No.15/497,726, filed Apr. 26, 2017, published as U.S. Patent ApplicationPublication No. 2018/0018515, entitled “IRIS BOUNDARY ESTIMATION USINGCORNEA CURVATURE,” which is incorporated by reference herein in itsentirety. Example eye tracking modules and techniques, which may beimplemented as the eye tracking module 614 or otherwise utilized by theeye tracking module 614, are described in U.S. Patent Application No.16/250,931, filed Jan. 17, 2019, published as U.S. Patent ApplicationPublication No. 2019/0243448, entitled “EYE CENTER OF ROTATIONDETERMINATION, DEPTH PLANE SELECTION, AND RENDER CAMERA POSITIONING INDISPLAY SYSTEMS,” which is incorporated by reference herein in itsentirety.

Image preprocessing module 710 may receive images from an eye camerasuch as eye camera 324 and may perform one or more preprocessing (e.g.,conditioning) operations on the received images. As examples, imagepreprocessing module 710 may apply a Gaussian blur to the images, maydown sample the images to a lower resolution, may applying an unsharpmask, may apply an edge sharpening algorithm, or may apply othersuitable filters that assist with the later detection, localization, andlabelling of glints, a pupil, or other features in the images from eyecamera 324. The image preprocessing module 710 may apply a low-passfilter or a morphological filter such as an open filter, which canremove high-frequency noise such as from the pupillary boundary 516 a(see FIG. 5 ), thereby removing noise that can hinder pupil and glintdetermination. The image preprocessing module 710 may outputpreprocessed images to the pupil identification module 712 and to theglint detection and labeling module 714.

Pupil identification module 712 may receive preprocessed images from theimage preprocessing module 710 and may identify regions of those imagesthat include the user’s pupil. The pupil identification module 712 may,in some embodiments, determine the coordinates of the position, orcoordinates, of the center, or centroid, of the user’s pupil in the eyetracking images from camera 324. In at least some embodiments, pupilidentification module 712 may identify contours in eye tracking images(e.g., contours of pupil iris boundary), identify contour moments (e.g.,centers of mass), apply a starburst pupil detection and/or a canny edgedetection algorithm, reject outliers based on intensity values, identifysub-pixel boundary points, correct for eye-camera distortion (e.g.,distortion in images captured by eye camera 324), apply a random sampleconsensus (RANSAC) iterative algorithm to fit an ellipse to boundariesin the eye tracking images, apply a tracking filter to the images, andidentify sub-pixel image coordinates of the user’s pupil centroid. Thepupil identification module 712 may output pupil identification data,which may indicate which regions of the preprocessing images module 712identified as showing the user’s pupil, to glint detection and labelingmodule 714. The pupil identification module 712 may provide the 2Dcoordinates of the user’s pupil (e.g., the 2D coordinates of thecentroid of the user’s pupil) within each eye tracking image to glintdetection module 714. In at least some embodiments, pupil identificationmodule 712 may also provide pupil identification data of the same sortto coordinate system normalization module 718.

Pupil detection techniques, which may be utilized by pupilidentification module 712, are described in U.S. Patent Publication No.2017/0053165, published Feb. 23, 2017 and in U.S. Patent Publication No.2017/0053166, published Feb. 23, 2017, each of which is incorporated byreference herein in its entirety.

Glint detection and labeling module 714 may receive preprocessed imagesfrom module 710 and pupil identification data from module 712. Glintdetection module 714 may use this data to detect and/or identify glints(e.g., reflections off of the user’s eye of the light from light sources326) within regions of the preprocessed images that show the user’spupil. As an example, the glint detection module 714 may search forbright regions within the eye tracking image, sometimes referred toherein as “blobs” or local intensity maxima that are in the vicinity ofthe user’s pupil or iris. In at least some embodiments, the glintdetection module 714 may rescale (e.g., enlarge) the pupil ellipse toencompass additional glints. The glint detection module 714 may filterglints by size or by intensity. The glint detection module 714 may alsodetermine the 2D positions of each of the glints within the eye trackingimage. In at least some examples, the glint detection module 714 maydetermine the 2D positions of the glints relative to the user’s pupil,which may also be referred to as the pupil-glint vectors. Glintdetection and labeling module 714 may label the glints and output thepreprocessing images with labeled glints to the 3D cornea centerestimation module 716. Glint detection and labeling module 714 may alsopass along data such as preprocessed images from module 710 and pupilidentification data from module 712. In some implementations, the glintdetection and labeling module 714 may determine which light source(e.g., from among a plurality of light sources of the system includinginfrared light sources 326 a and 326 b) produced each identified glint.In these examples, the glint detection and labeling module 714 may labelthe glints with information identifying the associated light source andoutput the preprocessing images with labeled glints to the 3D corneacenter estimation module 716.

Pupil and glint detection, as performed by modules such as modules 712and 714, can use any suitable techniques. As examples, edge detectioncan be applied to the eye image to identify glints, pupils, or irises.Edge detection can be applied by various edge detectors, edge detectionalgorithms, or filters. For example, a Canny Edge detector can beapplied to the image to detect edges such as in lines of the image.Edges may include points located along a line that correspond to thelocal maximum derivative. For example, the pupillary boundary 516 a orthe iris (limbic) boundary 512 a (see FIG. 5 ) can be located using aCanny edge detector. With the location of the pupil or iris determined,various image processing techniques can be used to detect the “pose” ofthe pupil 116. The pose can also be referred to as the gaze, pointingdirection, or the orientation of the eye. For example, the pupil may belooking leftwards towards an object, and the pose of the pupil could beclassified as a leftwards pose. Other methods can be used to detect thelocation of the pupil or glints. For example, a concentric ring can belocated in an eye image using a Canny Edge detector. As another example,an integro-differential operator can be used to find the pupillary orlimbus boundaries of the iris. For example, the Daugmanintegro-differential operator, the Hough transform, or other irissegmentation techniques can be used to return a curve that estimates theboundary of the pupil or the iris. The modules 712, 714 can apply theglint detection techniques described herein, which may use multiple eyeimages captured with different exposure times or different frame rates.

3D cornea center estimation module 716 may receive preprocessed imagesincluding detected glint data and pupil (or iris) identification datafrom modules 710, 712, 714. 3D cornea center estimation module 716 mayuse these data to estimate the 3D position of the user’s cornea. In someembodiments, the 3D cornea center estimation module 716 may estimate the3D position of an eye’s center of cornea curvature or a user’s cornealsphere, e.g., the center of an imaginary sphere having a surface portiongenerally coextensive with the user’s cornea. The 3D cornea centerestimation module 716 may provide data indicating the estimated 3Dcoordinates of the corneal sphere and/or user’s cornea to the coordinatesystem normalization module 718, the optical axis determination module722, and/or the light-field render controller 618. Techniques forestimating the positions of eye features such as a cornea or cornealsphere, which may be utilized by 3D cornea center estimation module 716and other modules in the wearable systems of the present disclosure arediscussed in U.S. Patent Application No. 15/497,726, filed Apr. 26,2017, published as U.S. Patent Application Publication No. 2018/0018515,which is incorporated by reference herein in its entirety.

Coordinate system normalization module 718 may optionally (as indicatedby its dashed outline) be included in eye tracking module 614.Coordinate system normalization module 718 may receive data indicatingthe estimated 3D coordinates of the center of the user’s cornea (and/orthe center of the user’s corneal sphere) from the 3D cornea centerestimation module 716 and may also receive data from other modules.Coordinate system normalization module 718 may normalize the eye cameracoordinate system, which may help to compensate for slippages of thewearable device (e.g., slippages of the head-mounted component from itsnormal resting position on the user’s head, which may be identified byregistration observer 620). Coordinate system normalization module 718may rotate the coordinate system to align the z-axis (e.g., the vergencedepth axis) of the coordinate system with the cornea center (e.g., asindicated by the 3D cornea center estimation module 716) and maytranslate the camera center (e.g., the origin of the coordinate system)to a predetermined distance away from the cornea center such as 30 mm(e.g., module 718 may enlarge or shrink the eye tracking image dependingon whether the eye camera 324 was determined to be nearer or furtherthan the predetermined distance). With this normalization process, theeye tracking module 614 may be able to establish a consistentorientation and distance in the eye tracking data, relativelyindependent of variations of headset positioning on the user’s head.Coordinate system normalization module 718 may provide 3D coordinates ofthe center of the cornea (and/or corneal sphere), pupil identificationdata, and preprocessed eye tracking images to the 3D pupil centerlocator module 720.

3D pupil center locator module 720 may receive data, in the normalizedor the unnormalized coordinate system, including the 3D coordinates ofthe center of the user’s cornea (and/or corneal sphere), pupil locationdata, and preprocessed eye tracking images. 3D pupil center locatormodule 720 may analyze such data to determine the 3D coordinates of thecenter of the user’s pupil in the normalized or unnormalized eye cameracoordinate system. The 3D pupil center locator module 720 may determinethe location of the user’s pupil in three-dimensions based on the 2Dposition of the pupil centroid (as determined by module 712), the 3Dposition of the cornea center (as determined by module 716), assumed eyedimensions 704 such as the size of the a typical user’s corneal sphereand the typical distance from the cornea center to the pupil center, andoptical properties of eyes such as the index of refraction of the cornea(relative to the index of refraction of air) or any combination ofthese. Techniques for estimating the positions of eye features such as apupil, which may be utilized by 3D pupil center locator module 720 andother modules in the wearable systems of the present disclosure arediscussed in U.S. Patent Application No. 15/497,726, filed Apr. 26,2017, published as U.S. Patent Application Publication No. 2018/0018515,which is incorporated by reference herein in its entirety.

Optical axis determination module 722 may receive data from modules 716and 720 indicating the 3D coordinates of the center of the user’s corneaand the user’s pupil. Based on such data, the optical axis determinationmodule 722 may identify a vector from the position of the cornea center(e.g., from the center of the corneal sphere) to the center of theuser’s pupil, which may define the optical axis of the user’s eye.Optical axis determination module 722 may provide outputs specifying theuser’s optical axis to modules 724, 728, 730, and 732, as examples.

Center of rotation (CoR) estimation module 724 may receive data frommodule 722 including parameters of the optical axis of the user’s eye(e.g., data indicating the direction of the optical axis in a coordinatesystem with a known relation to the head-mounted unit 602). CoRestimation module 724 may estimate the center of rotation of a user’seye (e.g., the point around which the user’s eye rotates when the usereye rotates left, right, up, and/or down). While eyes may not rotateperfectly around a singular point, assuming a singular point may besufficient. In at least some embodiments, CoR estimation module 724 mayestimate an eye’s center of rotation by moving from the center of thepupil (identified by module 720) or the center of curvature of thecornea (as identified by module 716) toward the retina along the opticalaxis (identified by module 722) a particular distance. This particulardistance may be an assumed eye dimension 704. As one example, theparticular distance between the center of curvature of the cornea andthe CoR may be approximately 4.7 mm. This distance may be varied for aparticular user based on any relevant data including the user’s age,gender, vision prescription, other relevant characteristics, etc.

In at least some embodiments, the CoR estimation module 724 may refineits estimate of the center of rotation of each of the user’s eyes overtime. As an example, as time passes, the user will eventually rotatetheir eyes (to look somewhere else, at something closer, further, orsometime left, right, up, or down) causing a shift in the optical axisof each of their eyes. CoR estimation module 724 may then analyze two(or more) optical axes identified by module 722 and locate the 3D pointof intersection of those optical axes. The CoR estimation module 724 maythen determine the center of rotation lies at that 3D point ofintersection. Such a technique may provide for an estimate of the centerof rotation, with an accuracy that improves over time. Varioustechniques may be employed to increase the accuracy of the CoRestimation module 724 and the determined CoR positions of the left andright eyes. As an example, the CoR estimation module 724 may estimatethe CoR by finding the average point of intersection of optical axesdetermined for various different eye poses over time. As additionalexamples, module 724 may filter or average estimated CoR positions overtime, may calculate a moving average of estimated CoR positions overtime, and/or may apply a Kalman filter and known dynamics of the eyesand eye tracking system to estimate the CoR positions over time. As aspecific example, module 724 may calculate a weighted average ofdetermined points of optical axes intersection and assumed CoR positions(such as 4.7 mm from an eye’s center of cornea curvature), such that thedetermined CoR may slowly drift from an assumed CoR position (e.g., 4.7mm behind an eye’s center of cornea curvature) to a slightly differentlocation within the user’s eye over time as eye tracking data for theuser is obtain and thereby enables per-user refinement of the CoRposition.

Interpupillary distance (IPD) estimation module 726 may receive datafrom CoR estimation module 724 indicating the estimated 3D positions ofthe centers of rotation of the user’s left and right eyes. IPDestimation module 726 may then estimate a user’s IPD by measuring the 3Ddistance between the centers of rotation of the user’s left and righteyes. In general, the distance between the estimated CoR of the user’sleft eye and the estimated CoR of the user’s right eye may be roughlyequal to the distance between the centers of a user’s pupils, when theuser is looking at optical infinity (e.g., the optical axes of theuser’s eyes are substantially parallel to one another), which is thetypical definition of interpupillary distance (IPD). A user’s IPD may beused by various components and modules in the wearable system. Asexample, a user’s IPD may be provided to registration observer 620 andused in assessing how well the wearable device is aligned with theuser’s eyes (e.g., whether the left and right display lenses areproperly spaced in accordance with the user’s IPD). As another example,a user’s IPD may be provided to vergence depth estimation module 728 andbe used in determining a user’s vergence depth. Module 726 may employvarious techniques, such as those discussed in connection with CoRestimation module 724, to increase the accuracy of the estimated IPD. Asexamples, IPD estimation module 724 may apply filtering, averaging overtime, weighted averaging including assumed IPD distances, Kalmanfilters, etc. as part of estimating a user’s IPD in an accurate manner.

In some embodiments, IPD estimation module 726 may receive data from 3Dpupil center locator module and/or 3D cornea center estimationmodulation 716 indicating the estimated 3D positions of the user’spupils and/or corneas. IPD estimation module 726 may then estimate auser’s IPD by reference to the distances between the pupils and corneas.In general, these distances will vary over time as a user rotates theireyes and changes the depth of their vergence. In some cases, the IPDestimation module 726 may look for the largest measured distance betweenthe pupils and/or corneas, which can occur while the user is lookingnear optical infinity and generally corresponds to the user’sinterpupillary distance. In other cases, the IPD estimation module 726may fit the measured distances between the user’s pupils (and/orcorneas) to a mathematical relationship of how a person’s interpupillarydistance changes as a function of their vergence depth. In someembodiments, using these or other similar techniques, the IPD estimationmodule 726 may be able to estimate the user’s IPD even without anobservation of the user looking at optical infinity (e.g., byextrapolating out from one or more observations in which the user wasverging at distances closer than optical infinity).

Vergence depth estimation module 728 may receive data from variousmodules and submodules in the eye tracking module 614 (as shown inconnection with FIG. 7 ). In particular, vergence depth estimationmodule 728 may employ data indicating estimated 3D positions of pupilcenters (e.g., as provided by module 720 described above), one or moredetermined parameters of optical axes (e.g., as provided by module 722described above), estimated 3D positions of centers of rotation (e.g.,as provided by module 724 described above), estimated IPD (e.g.,Euclidean distance(s) between estimated 3D positions of centers ofrotations) (e.g., as provided by module 726 described above), and/or oneor more determined parameters of optical and/or visual axes (e.g., asprovided by module 722 and/or module 730 described below). Vergencedepth estimation module 728 may detect or otherwise obtain a measure ofa user’s vergence depth, which may be the distance from the user atwhich the user’s eyes are focused. As examples, when the user is lookingat an object three feet in front of them, the user’s left and right eyeshave a vergence depth of three feet; and, while when the user is lookingat a distant landscape (e.g., the optical axes of the user’s eyes aresubstantially parallel to one another such that the distance between thecenters of the user’s pupils may be roughly equal to the distancebetween the centers of rotation of the user’s left and right eyes), theuser’s left and right eyes have a vergence depth of infinity. In someimplementations, the vergence depth estimation module 728 may utilizedata indicating the estimated centers of the user’s pupils (e.g., asprovided by module 720) to determine the 3D distance between theestimated centers of the user’s pupils. The vergence depth estimationmodule 728 may obtain a measure of vergence depth by comparing such adetermined 3D distance between pupil centers to estimated IPD (e.g.,Euclidean distance(s) between estimated 3D positions of centers ofrotations) (e.g., as indicated by module 726 described above). Inaddition to the 3D distance between pupil centers and estimated IPD, thevergence depth estimation module 728 may utilize known, assumed,estimated, and/or determined geometries to calculate vergence depth. Asan example, module 728 may combine 3D distance between pupil centers,estimated IPD, and 3D CoR positions in a trigonometric calculation toestimate (e.g., determine) a user’s vergence depth. Indeed, anevaluation of such a determined 3D distance between pupil centersagainst estimated IPD may serve to indicate a measure of the user’scurrent vergence depth relative to optical infinity. In some examples,the vergence depth estimation module 728 may simply receive or accessdata indicating an estimated 3D distance between the estimated centersof the user’s pupils for purposes of obtaining such a measure ofvergence depth. In some embodiments, the vergence depth estimationmodule 728 may estimate vergence depth by comparing a user’s left andright optical axis. In particular, vergence depth estimation module 728may estimate vergence depth by locating the distance from a user atwhich the user’s left and right optical axes intersect (or whereprojections of the user’s left and right optical axes on a plane such asa horizontal plane intersect). Module 728 may utilize a user’s IPD inthis calculation, by setting the zero depth to be the depth at which theuser’s left and right optical axes are separated by the user’s IPD. Inat least some embodiments, vergence depth estimation module 728 maydetermine vergence depth by triangulating eye tracking data togetherwith known or derived spatial relationships.

In some embodiments, vergence depth estimation module 728 may estimate auser’s vergence depth based on the intersection of the user’s visualaxes (instead of their optical axes), which may provide a more accurateindication of the distance at which the user is focused on. In at leastsome embodiments, eye tracking module 614 may include optical to visualaxis mapping module 730. As discussed in further detail in connectionwith FIGS. 10 , a user’s optical and visual axis are generally notaligned. A visual axis is the axis along which a person is looking,while an optical axis is defined by the center of that person’s lens andpupil, and may go through the center of the person’s retina. Inparticular, a user’s visual axis is generally defined by the location ofthe user’s fovea, which may be offset from the center of a user’sretina, thereby resulting in different optical and visual axis. In atleast some of these embodiments, eye tracking module 614 may includeoptical to visual axis mapping module 730. Optical to visual axismapping module 730 may correct for the differences between a user’soptical and visual axis and provide information on the user’s visualaxis to other components in the wearable system, such as vergence depthestimation module 728 and light-field render controller 618. In someexamples, module 730 may use assumed eye dimensions 704 including atypical offset of approximately 5.2° inwards (nasally, towards a user’snose) between an optical axis and a visual axis. In other words, module730 may shift a user’s left optical axis (nasally) rightwards by 5.2°towards the nose and a user’s right optical axis (nasally) leftwards by5.2° towards the nose in order to estimate the directions of the user’sleft and right optical axes. In other examples, module 730 may utilizeper-user calibration data 706 in mapping optical axes (e.g., asindicated by module 722 described above) to visual axes. As additionalexamples, module 730 may shift a user’s optical axes nasally by between4.0° and 6.5°, by between 4.5° and 6.0°, by between 5.0° and 5.4°, etc.,or any ranges formed by any of these values. In some arrangements, themodule 730 may apply a shift based at least in part upon characteristicsof a particular user such as their age, sex, vision prescription, orother relevant characteristics and/or may apply a shift based at leastin part upon a calibration process for a particular user (e.g., todetermine a particular user’s optical-visual axis offset). In at leastsome embodiments, module 730 may also shift the origins of the left andright optical axes to correspond with the user’s CoP (as determined bymodule 732) instead of the user’s CoR.

Optional center of perspective (CoP) estimation module 732, whenprovided, may estimate the location of the user’s left and right centersof perspective (CoP). A CoP may be a useful location for the wearablesystem and, in at least some embodiments, is a position just in front ofa pupil. In at least some embodiments, CoP estimation module 732 mayestimate the locations of a user’s left and right centers of perspectivebased on the 3D location of a user’s pupil center, the 3D location of auser’s center of cornea curvature, or such suitable data or anycombination thereof. As an example, a user’s CoP may be approximately5.01 mm in front of the center of cornea curvature (e.g., 5.01 mm fromthe corneal sphere center in a direction that is towards the eye’scornea and that is along the optical axis) and may be approximately 2.97mm behind the outer surface of a user’s cornea, along the optical orvisual axis. A user’s center of perspective may be just in front of thecenter of their pupil. As examples, a user’s CoP may be less thanapproximately 2.0 mm from the user’s pupil, less than approximately 1.0mm from the user’s pupil, or less than approximately 0.5 mm from theuser’s pupil or any ranges between any of these values. As anotherexample, the center of perspective may correspond to a location withinthe anterior chamber of the eye. As other examples, the CoP may bebetween 1.0 mm and 2.0 mm, about 1.0 mm, between 0.25 mm and 1.0 mm,between 0.5 mm and 1.0 mm, or between 0.25 mm and 0.5 mm.

The center of perspective described herein (as a potentially desirableposition for a pinhole of a render camera and an anatomical position ina user’s eye) may be a position that serves to reduce and/or eliminateundesired parallax shifts. In particular, the optical system of a user’seye is very roughly equivalent to theoretical system formed by a pinholein front of a lens, projecting onto a screen, with the pinhole, lens,and screen roughly corresponding to a user’s pupil/iris, lens, andretina, respectively. Moreover, it may be desirable for there to belittle or no parallax shift when two point light sources (or objects) atdifferent distances from the user’s eye are rigidly rotated about theopening of the pinhole (e.g., rotated along radii of curvature equal totheir respective distance from the opening of the pinhole). Thus, itwould seem that the CoP should be located at the center of the pupil ofan eye (and such a CoP may be used in some embodiments). However, thehuman eye includes, in addition to the lens and pinhole of the pupil, acornea that imparts additional optical power to light propagating towardthe retina). Thus, the anatomical equivalent of the pinhole in thetheoretical system described in this paragraph may be a region of theuser’s eye positioned between the outer surface of the cornea of theuser’s eye and the center of the pupil or iris of the user’s eye. Forinstance, the anatomical equivalent of the pinhole may correspond to aregion within the anterior chamber of a user’s eye. For various reasonsdiscussed herein, it may be desired to set the CoP to such a positionwithin the anterior chamber of the user’s eye.

As discussed above, eye tracking module 614 may provide data, such asestimated 3D positions of left and right eye centers of rotation (CoR),vergence depth, left and right eye optical axis, 3D positions of auser’s eye, 3D positions of a user’s left and right centers of corneacurvature, 3D positions of a user’s left and right pupil centers, 3Dpositions of a user’s left and right center of perspective, a user’sIPD, etc., to other components, such as light-field render controller618 and registration observer 620, in the wearable system. Eye trackingmodule 614 may also include other submodules that detect and generatedata associated with other aspects of a user’s eye. As examples, eyetracking module 614 may include a blink detection module that provides aflag or other alert whenever a user blinks and a saccade detectionmodule that provides a flag or other alert whenever a user’s eyesaccades (e.g., quickly shifts focus to another point).

Examples of Locating Glints with an Eye Tracking System

FIG. 8A is a schematic diagram of a cross-section of an eye showing theeye’s cornea 820, iris 822, lens 824, and pupil 826. The sclera (thewhite of the eye) surrounds the iris 822. The cornea can have anapproximately spherical shape, shown by corneal sphere 802, which has acenter 804. The eye optical axis is a line (shown by a solid line 830)passing through the center 806 of the pupil and the cornea center 804.The user’s gaze direction (shown by a dashed line 832; sometimes alsoreferred to as a gaze vector) is the vision axis of the user andgenerally is at a small offset angle from the eye optical axis. Theoffset, which is specific to each particular eye, can be determined byuser calibration from eye images. The user-measured offset can be storedby a wearable display system and used to determine the gaze directionfrom measurements of the eye optical axis.

Light sources 326 a and 326 b (such as light emitting diodes, LEDs) canilluminate the eye and generate glints (e.g., specular reflections offof the user’s eye) that are imaged by a camera 324 a. Schematic examplesof glints 550 are shown in FIG. 5 . The positions of the light sources326 a and 326 b relative to the camera 324 is known and, as aconsequence, the positions of the glints within images captured bycamera 324 can be used in tracking the user’s eye as well as modelingthe corneal sphere 802 and determining its center 804. FIG. 8B is aphotograph of an eye showing an example of four glints 550, which areproduced by four light sources (for this example photograph). Generally,the light sources 326 a, 326 b produce infrared (IR) light, so that theuser does not see the light sources, which can be distracting.

In some eye tracking systems, a single image of the eye is used todetermine information about the pupil (e.g., to determine its center)and the glints (e.g., their positions in the eye image). As will befurther described below, measurements of both the pupil information andthe glint information from a single exposure can lead to errors indetermination of the eye optical axis or gaze, because, for example,images of the glints may be saturated in an image that also showssufficient detail to extract pupil information.

Examples of such errors are schematically illustrated in FIGS. 9A-9C. InFIGS. 9A-9C, the real gaze vector is shown as a solid line 830 passingthrough the pupil center 806 and the center 804 of the corneal sphere802, and the gaze vector extracted from an eye image is shown as adashed line 930. FIG. 9A shows an example of the error in the extractedgaze vector when there is a small error 900 a in the measured positionof only the pupil center. FIG. 9B shows an example of the error in theextracted gaze vector when there is a small error 900 b in the measuredposition of only the corneal center. FIG. 9C shows an example of theerror in the extracted gaze vector when there is a small error 900 a inthe measured position of the pupil center and a small error 900 b in themeasured position of the corneal center. In some embodiments of thewearable system 200, the error in gaze determination may be about 20arcminutes for each pixel of error in determination of a glint in theeye image, whereas with some embodiments of the multiple exposure timeeye tracking techniques described herein, the error can be reduced toless than about 3 arcminutes per pixel.

Eye Imaging Using Multiple Images with Different Exposure Times

FIG. 10A shows an example of uncertainty in a glint position when glintsare obtained from a single, long exposure eye image 1002 a. In thisexample, the exposure time for the eye image 1002 a was about 700 µs.One of the glints in the image 1002 a is shown in a zoomed-in image 1006a, and contour plot 1008 a shows intensity contours of the glint. Thezoomed-in image 1006 a shows that the glint is saturated, and the peakof the glint intensity is clipped. The dynamic range of the intensity inthe image 1006 a may be relatively high to capture both the lowerintensity pupil and iris features as well as the higher intensityglints. The glint covers many pixels in the image 1006 a, which may makeit challenging to accurately determine a center of the glint,particularly when the peak intensities of the glint are clipped. Thefull width half maximum (FWHM) of the glint 1006 a is about 15 pixels.For some embodiments of the wearable system 200, each pixel of error indetermining the center (or centroid) of the glint corresponds to about20 arcminutes of error in determining gaze direction or direction of theeye optical axis. Embodiments of eye imaging using multiple eye imagescaptured with different exposure times advantageously can identify glintpositions more accurately and advantageously can reduce the error ingaze direction or optical axis direction to a few arcminutes or less.

FIG. 10B shows an example of uncertainty in a glint position whentechniques using multiple images taken at different exposure times areused. In this example, two sequential images are captured by theeye-tracking camera: a first, longer exposure image 1002 b and a second,shorter exposure image 1004. The total capture time for the two images1002 b, 1004 is about 1.5 ms. The labels first and second as applied tothe images 1002 b and 1004 are not intended to indicate a temporal orderof when the images are taken but simply as a convenient way to refer toeach of the two images. Accordingly, the first image 1002 b can be takenbefore the second image 1004, after the second image 1004, or the twoexposures may at least partially overlap.

The longer exposure image 1002 b may have an exposure time similar tothe image 1002 a shown in FIG. 10A, which in this example is about 700µs. The first, longer exposure image 1002 b can be used to determinepupil (or iris) features. For example, the longer exposure image 1002 bcan be analyzed to determine the pupil center or center of rotation(CoR), extract iris features for biometric security applications,determine eyelid shape or occlusion of the iris or pupil by the eyelid,measure pupil size, determine render camera parameters, and so forth.However, as described with reference to FIG. 10A, the glints may besaturated in such a longer exposure image, which may lead to relativelylarge errors in glint positions.

In some implementations, pupil contrast in the longer exposure image canbe increased by using eye-tracking cameras that have a better modulationtransfer function (MTF), e.g., an MTF closer to a diffraction-limitedMTF. For example, a better MTF for the imaging sensor or a better MTFfor the imaging lens of the camera can be selected to improve pixelcontrast. Example imaging sensing devices and techniques, which may beimplemented as eye-tracking cameras having such an MTF or otherwiseemployed in one or more of the eye-tracking systems described herein,are described in U.S. Patent Application No. 16/219,829, filed Dec. 13,2018, published as U.S. Patent Application Publication No. 2019/0181171,entitled “GLOBAL SHUTTER PIXEL CIRCUIT AND METHOD FOR COMPUTER VISIONAPPLICATIONS,” and U.S. Patent Application No. 16/219,847, filed Dec.13, 2018, published as U.S. Patent Application Publication No.2019/0181169, entitled “DIFFERENTIAL PIXEL CIRCUIT AND METHOD OFCOMPUTER VISION APPLICATIONS,” both of which are incorporated byreference herein in their entirety. In various embodiments, theeye-tracking camera 324 can produce images with pupil contrast (e.g.,measured at the transition between the pupil and the iris) of 5 to 6pixels, 1 to 4 pixels, etc. Additional example imaging sensing devicesand techniques, which may be implemented as the eye-tracking camera 324or otherwise employed in one or more of the eye-tracking systemsdescribed herein in some embodiments, are described in U.S. PatentApplication No. 15/159,491, filed May 19, 2016, published as U.S. PatentApplication Publication No. 2016/0344957, entitled “SEMI-GLOBAL SHUTTERIMAGER,” which is incorporated by reference herein in its entirety.

The exposure time for the second, shorter exposure image 1004 can besubstantially less than the exposure time of the first image 1002 b toreduce the likelihood of saturating the glints 550 (e.g., clipping theglint peaks in the image). As noted above, the second, shorter exposureimage 1004 is sometimes referred to herein as a glint image as it can beused to identify glint positions accurately. In this example, theexposure time of the second image 1004 was less than 40 µs. Notice thatalthough the glints are perceptible in the second image 1004, the pupil(or iris) features are not readily perceptible, which is why the longerexposure first image 1002 b can be used for pupil center extraction orCoR determination. Image 1006 b is a zoomed-in view of one of the glintsin the second image 1004. The smaller size of the glint in the image1006 b (compared to the size in the image 1006 a) is readily apparent,which demonstrates that the glint is not saturated in the image 1006 b.Contour plot 1008 b shows a much smaller contour pattern for the glint(compared to the contours shown in the contour plot 1008 a). In thisexample, the location of the center of the glint can be determined tosubpixel accuracy, e.g., about ⅒th of a pixel (corresponding to onlyabout 2 arcminutes of error in gaze or optical axis direction in thisexample). In some implementations, the location of the pixel center canbe determined very accurately from the second, shorter exposure image1004, e.g., by fitting a two-dimensional (2D) Gaussian (or otherbell-shaped curve) to the glint pixel values. In some embodiments, thelocation of the center of mass of the glint can be determined and reliedupon in a capacity similar to that of the location of the center of theglint. The exposure times of the glint images used to determine glintlocations can be selected to be just long enough to image peaks of theglints.

Eye-imaging techniques thus may utilize capture of a longer exposureimage (which may be used for extraction of pupil properties) and ashorter exposure glint image (which may be used for extraction of glintposition). As noted above, the longer and shorter images can be taken inany order, or the exposure times can at least partially overlap. Theexposure time for the first image may be in a range from 200 µs to 1200µs, while the exposure time for the second image may be in a range from5 µs to 100 µs. The ratio of the exposure time for the first imagerelative to the exposure time for the second image can be in a rangefrom 5 to 50, 10 to 20, or some other range. The frame rates at whichthe longer and shorter exposure images can be captured are describedwith reference to FIG. 11 .

A potential advantage to determining glint positions from the second,shorter exposure image is that the glints cover a relatively smallnumber of pixels (e.g., compare the image 1006 b with the image 1006 a)and finding the glint center can be performed computationally quicklyand efficiently. For example, the search area for glints may have adiameter of only about 2 to 10 pixels, in some embodiments. Further,since the glints cover a smaller number of pixels, only a relativelysmall portion of the image may be analyzed or stored (e.g., in abuffer), which can provide substantial memory savings. Additionally, thedynamic range of the glint images may be sufficiently low that images ofambient, environmental light sources (e.g., room lights, the sky, etc.)are not perceptible due to the short exposure time, which advantageouslymeans that such ambient light sources will not interfere with or bemistaken for a glint.

Furthermore, using a relatively short exposure time may also serve toreduce the presence of motion blur in images of eyes engaged in saccadicor otherwise rapid movement. Example eye-tracking and saccade-detectingsystems and techniques, as well as exposure time switching andadjustment schemes associated therewith, are described in U.S.Provisional Patent Application No. 62/660,180, filed Apr. 19, 2018,entitled “SYSTEMS AND METHODS FOR ADJUSTING OPERATIONAL PARAMETERS OF AHEAD-MOUNTED DISPLAY SYSTEM BASED ON USER SACCADES,” and U.S. PatentApplication No. 16/389,529, filed Apr. 19, 2019, published as U.S.Patent Application Publication No. 2019/0324276, entitled “SYSTEMS ANDMETHODS FOR OPERATING A DISPLAY SYSTEM BASED ON USER PERCEPTIBILITY,”which are incorporated by reference herein in their entireties. In someimplementations, one or more of such example systems, techniques, andschemes may be implemented as or otherwise leveraged in one or more ofthe systems and techniques described herein (e.g., by the eye trackingmodule 614). Additional details of switching between shorter time andlonger time exposures are described below with reference to FIG. 11 .

As described above, in some implementations, at least a portion of aglint image is temporarily stored in a buffer and that portion of theglint image is analyzed to identify positions of one or more glints thatmay be located in that portion. For example, the portion may comprise arelatively small number of pixels, rows, or columns of the glint image.In some cases, the portion may comprise an n x m portion of the glintimage, where n and m are in a range from about 1 to 20. For example, a5x5 portion of the glint image may be stored in the buffer.

After the positions of the glint(s) are identified, the buffer may becleared. An additional portion of the glint image may then be stored inthe buffer for analysis, until either the entire glint image has beenprocessed or all the glints (commonly, four) have been identified. Insome cases, more than one of the glints of the image are in the bufferat the same time for processing. In some cases, the majority of theglints of the image are in the buffer at the same time for processing.In some cases, all the glints of the image are in the buffer at the sametime for processing. The glint positions (e.g., Cartesian coordinates)may be used for subsequent actions in the eye-tracking process, andafter the glint positions have been stored or communicated to a suitableprocessor, the glint image may be deleted from memory (buffer memory orother volatile or non-volatile storage). Such buffering mayadvantageously permit rapid processing of the glint image to identifyglint positions or reduce storage needs of the eye-tracking processsince the glint image may be deleted after use.

In some implementations, the shorter exposure, glint images areprocessed by a hardware processor in the wearable system 200, 400, or600. For example, the glint images may be processed by the CPU 612 ofthe head-mounted unit 602 described with reference to FIG. 6 . The CPU612 may include or be in communication with a buffer 615, which can beused to temporarily store at least a portion of the glint image forprocessing (e.g., identifying glint positions). The CPU 612 may, in someimplementations, output the positions of the identified glints toanother processor that analyzes the longer exposure image (e.g., the CPU616 or the GPU 620 described with reference to FIG. 6 ). This otherprocessor may, in some implementations, be remote from the head-mounteddisplay unit. The other processor may, for example, be in the belt pack.Accordingly, in some implementations, a hardware processor such as theCPU 612 may output the positions of the identified glints (e.g.,Cartesian coordinates of the glint peaks) possibly along with dataindicative of the intensities of the identified glints (e.g., peakintensities of the glints) to another processor (e.g., the CPU 616 orthe GPU 620 described with reference to FIG. 6 ). In some embodiments,the CPU 612 and the buffer 615 are in a hardware processor that is in orassociated with the eye-tracking camera 324. Such an arrangement canprovide for increased efficiency, because the shorter exposure glintimages can be processed by the camera circuitry and do not need to becommunicated to another processing unit (either on or off of thehead-mounted unit 602). The camera 324 may simply output glint positions(e.g., Cartesian coordinates of the glint peaks) to another processingunit (e.g., a hardware processor that analyzes the longer exposureimages such as the CPU 612, 616 or the GPU 620). Accordingly, in someembodiments, a hardware processor that is in or associated with thecamera 324 may output the positions of the identified glints (e.g.,Cartesian coordinates of the glint peaks) possibly along with dataindicative of the intensities of each of the identified glints (e.g.,peak intensities of the glints) to another processor (e.g., the CPU 612,616, or the GPU 620 described with reference to FIG. 6 ). In someimplementations, the shorter exposure, glint images are processed by ahardware processor (e.g., CPU 612), and this hardware processor mayoutput the positions of identified glint candidates (e.g., Cartesiancoordinates of the glint peaks), which may potentially be glint images,possibly along with data indicative of the intensities of the identifiedglint candidates (e.g., peak intensities of the glints) to anotherprocessor. This other processor may identify a subset of the identifiedglint candidates as glints. This other processor may also perform one ormore operations (e.g., one or more operations to determine gazedirection) on the basis of the subset of the identified glint candidates(e.g., the subset of the identified glint candidates deemed to be glintsby the other processor). Accordingly, in some implementations, theshorter exposure, glint images are processed by a hardware processor(e.g., CPU 612, a hardware processor that is in or associated with thecamera 324, etc.), and this hardware processor may output the positionsof the identified glint candidates (e.g., Cartesian coordinates of theglint peaks) possibly along with data indicative of the intensities ofthe identified glint candidates (e.g., peak intensities of the glints)to another processor (e.g., the CPU 616 or the GPU 620 described withreference to FIG. 6 ), and this other processor (e.g., the CPU 616 orthe GPU 620 described with reference to FIG. 6 ) may perform one or moreoperations (e.g., one or more operations to determine gaze direction) onthe basis of a subset of the identified glint candidates (e.g., a subsetof the identified glint candidates deemed to be glints by the otherprocessor). In some implementations, the hardware processor thatprocesses the shorter exposure, glint images may further output dataindicative of the intensities of the different identified glintcandidates (e.g., peak intensities of the glints) to the other processor(e.g., the CPU 616 or the GPU 620 described with reference to FIG. 6 )and, in some examples, this other processor may select a subset of theidentified glint candidates based on one or both of the positions of theidentified glint candidates and the intensities of the identified glintcandidates and may possibly further perform one or more operations(e.g., one or more operations to determine gaze direction) on the basisof the selected subset of identified glint candidates. For instance, inat least some of these implementations, the other processor (e.g., theCPU 616 or the GPU 620 described with reference to FIG. 6 ) maydetermine a gaze direction of an eye based at least in part on theselected subset of identified glint candidates and the center of thepupil of said eye (e.g., as determined by the other processor based onone or more longer exposure images). In some implementations, the subsetof identified glint candidates selected by the other processor may onlyinclude one glint candidate for each infrared light source employed bythe system, while the quantity of glint candidates identified andcommunicated to the other processor may exceed the quantity of infraredlight sources that are employed by the system. Other configurations andapproaches are possible.

In various implementations, the longer exposure image may be processedby the CPU 612 or may be communicated to the non-head mounted unit 604,e.g., for processing by the CPU 616 or the GPU 621. As noted, in someimplementations, the CPU 616 or the GPU 621 may obtain the glintpositions identified from the shorter exposure image from anotherprocessor (e.g., the CPU 612) programmed to analyze the glint imagesstored by the buffer 615.

Frame Rates for Multiple Exposure Time Eye Imaging

As described above, capturing multiple eye images with differentexposure times advantageously can provide accurate determination ofglint centers (e.g., from the shorter exposure image) and accuratedetermination of pupil center (e.g., from the longer exposure image).The positions of the glint centers can be used to determine the pose ofthe cornea.

As the user’s eye moves, the glints will correspondingly move. To trackeye movement, multiple short glint exposures can be taken to capture themotion of the glints. Accordingly, embodiments of the eye-trackingsystem can capture glint exposures at a relatively high frame rate(e.g., compared to the frame rate of the longer exposure images), forexample, in a range from about 100 frames per second (fps) to 500 fps.Thus, a time period between successive short glint exposures may be in arange from about 1 to 2 ms up to about 5 to 10 ms, in variousembodiments.

The longer exposure images for pupil center determination may becaptured at a lower frame rate than the frame rate for the glint images.For example, the frame rate for the longer exposure images can be in arange from about 10 fps to 60 fps, in various embodiments. This is not arequirement, and in some embodiments, the frame rates of both theshorter and longer exposure images are the same.

FIG. 11 shows an example of a combined operational mode in which thelonger exposure images are taken at a frame rate of 50 fps (e.g., 20 msbetween successive images), and the glint images are taken at a framerate of 200 fps (e.g., 5 ms between successive glint images). Thecombined operational mode may be performed by the eye tracking modules614 described with reference to FIGS. 6 and 7 . The horizontal axis inFIG. 11 is time (in ms). The top row of FIG. 11 schematicallyillustrates illumination of the eye (e.g., by an IR light source) andcapture of the corresponding image, e.g., by the eye-tracking camera324. Glint images 1004 are illustrated as pointed triangles, whereas thelonger exposure images are illustrated as wider, flat topped trapezoids.In this example, the glint image is capture before a subsequent longexposure image, although the order can be reversed in otherimplementations. Because, in this example, the frame rate for the glintimages 1004 is higher than the frame rate for the longer exposure images1002 (e.g., four times higher in this example), FIG. 11 shows four glintimages being captured (separated by about 5 ms) before the next longerexposure image is taken (e.g., 20 ms after the first longer exposureimage was captured).

In other implementations, the glint image frame rate or the longerexposure image frame rate could be different than illustrated in FIG. 11. For example, the glint image frame rate can be in a range from about100 fps to about 1000 fps, and the longer exposure image frame rate canbe in a range from about 10 fps to about 100 fps. In variousembodiments, the ratio of the glint image frame rate to the longerexposure frame rate can in a range from about 1 to 20, 4 to 10, or someother range.

The middle row of FIG. 11 schematically illustrates readout of the glintand longer exposure image data (with readout occurring after the imageis captured), and the bottom row of FIG. 11 shows an operational mode ofthe eye-tracking system (e.g., glint priority using glint images orpupil priority using longer exposure images). Thus, in this example,glint positions are determined every 5 ms from the short exposure glintimages, and pupil center (or CoR) is determined every 20 ms from thelonger exposure images. The exposure time of the longer exposure imagesmay be long enough and have sufficient dynamic range to capture thepupil and iris features but short enough so that the eye has not movedsubstantially during the exposure (e.g., to reduce the likelihood ofblurring in the image). As noted above, the exposure time of the longerexposure images can be about 700 µs and the exposure time of the glintimages can be less than about 40 µs, in some embodiments.

In some embodiments, the eye tracking module 614 may dynamically adjustthe exposure time, for example, between the shorter exposure time andthe longer exposure time. For example, an exposure time may be selectedby the display system (e.g., from a range of exposure times) based on atype of information being determined. As an example, the eye trackingmodule 614 may be determining occurrence of a saccade. In other exampleshowever, the wearable display system 200 may obtain one or more imagesto determine a gaze associated with the user’s eye. For example, thedisplay system may utilize a geometry of the user’s eye to determine avector extending from the user’s fovea or the eye optical axis describedwith reference to FIG. 8A. The display system may therefore select ashorter exposure time to reduce existence of motion blur. Additionally,the display system may perform a biometric authentication process basedon an image of the user’s eye. For example, the display system maycompare known eye features of the user’s user to eye features identifiedin the image. Thus, the display system may similarly select a shorterexposure time to reduce existence of motion blur.

When dynamically adjusting the exposure time, the eye tracking module614 may alternate between obtaining images at a first exposure time(e.g., a long exposure) and obtaining images at a second exposure time(e.g., a short exposure). For example, the eye tracking module mayobtain an image at the first exposure time to determine whether the useris performing a saccade, and then subsequently obtain an image at thesecond exposure time. Additionally, particular operating conditions ofthe wearable display system 200 may inform whether images are to beobtained at the first or second exposure time.

In some embodiments, the eye tracking module 614 may dynamically adjustone or more of the exposure times. For example, the eye tracking modulemay increase or decrease the exposure time used for saccade detection orglint positions. In this example, the eye tracking module may determinethat measures associated with motion blur are too high or too low. Thatis, the measures may not be accurately detecting, or over detecting,saccades due to the exposure time. For example, the eye tracking modulemay be configured to perform saccade detection using both motion blurdetection and comparisons between successively-captured image frames.Assuming that the comparisons between image frames provide more accuratedetermination of the occurrence of saccades, the results provided bycomparing multiple images may be used as a reference, and the motionblur detection may be adjusted until a desired (e.g., high) level ofagreement is reached between the results of the two schemes for saccadedetection. If the image frame comparison indicates that saccades arebeing under detected, the eye tracking module may be configured toincrease the exposure time. Conversely, if saccades are being falselydetected, then the exposure time may be decreased.

The eye tracking module may additionally or alternatively dynamicallyadjust the exposure time for the longer exposure images used fordetermining pupil or iris properties (e.g., pupil center, CoR, etc.).For example, if the longer exposure image has such a high dynamic rangethat iris details are saturated, the eye tracking module may decreasethe exposure time.

In some embodiments, when performing a biometric authentication process,or when determining a gaze of the user, the eye tracking module may alsoadjust the exposure time. For example, the display system maydynamically reduce the exposure time to reduce motion blur, or the eyetracking module may increase the exposure time if the obtained imagesare not properly exposed (e.g., if the images are too dark).

In some embodiments, the eye tracking module may utilize the same camerafor each image obtained of the user’s eye (e.g., the camera 324). Thatis, the eye tracking module may utilize a camera pointing at aparticular eye of the user. When a user performs a saccade, both eyesmay move in a corresponding manner (e.g., at a similar velocity andamplitude). Thus, the eye tracking module may utilize images of the sameeye to reliably determine whether a saccade is being performed.Optionally, the eye tracking module may utilize cameras pointing at eacheye of the user. In such embodiments, the eye tracking module mayoptionally utilize the same camera to obtain images of the same eye ormay select a camera to utilize. For example, the eye tracking module mayselect a camera that is not being currently utilized. The eye trackingmodule may obtain images of the user’s eyes for purpose other thandetermining the occurrence of saccades. As an example, the eye trackingmodule may perform gaze detection (e.g., the eye tracking module maydetermine a three-dimensional point at which the user is fixating),prediction of future gaze direction (e.g., for foveated rendering),biometric authentication (e.g., the eye tracking module may determinewhether a user’s eye matches with a known eye), and so on. In someembodiments, when the eye tracking module provides a command that animage is to be taken, one of the cameras may be in use. Therefore, theeye tracking module may select a camera not in use to obtain the imageto be used for saccade detection, gaze direction determination, glintidentification, biometric authentication, etc.

Optionally, the eye tracking module may trigger both cameras to obtainimages at the same time. For example, each camera may obtain an image ata respective exposure time. In this way, the eye tracking module mayobtain a first image of a first eye to determine measures of motionblur, glint positions, etc., while obtaining a second image of a secondeye to determine other information (e.g., information to be used forgaze detection, pupil center determination, authentication, and so on).Optionally, both images may be utilized to determine whether the user isperforming a saccade. For example, the eye tracking module may determinedeformation of features (e.g., an eye of the user, a glint, and so on)shown in a first image as compared to the same features as shown in asecond image. Optionally, the eye tracking module may cause each camerato alternate between two exposure values, for example out of phase fromeach other. For example, a first camera may obtain an image at a firstexposure value (e.g., a shorter exposure time), and at the same time asecond camera may obtain an image at a second exposure value (e.g., alonger exposure time). Subsequently, the first camera may obtain animage at the second exposure value, and the second camera may obtain animage at the first exposure value.

Glint Motion Detector

FIG. 12 schematically illustrates an example of how the use of shortexposure glint images captured at relatively high frame rates canprovide robust glint detection and tracking as the eye moves. In Frame#1, four example glints are shown. Frame #2 is a glint image taken ashort time after Frame #1 (e.g., about 5 ms later at a 200 fps rate) andillustrates how the initial glint positions (labeled as #1) have movedto positions labeled by #2. Likewise, Frame #3 is another glint imagetaken a short time after Frame #2 (e.g., about 5 ms later at a 200 fpsrate) and illustrates how the initial glint positions have continuedmove to positions labeled by #3. Note that in Frame #2 only glints atpositions labeled #2 would appear in the image, glints at positionslabeled #1 are shown for reference, and likewise for Frame #3.Accordingly, FIG. 12 schematically shows how an example constellation orpattern of glints moves from frame to frame.

Because the glint images can be captured at a relatively high framerate, determination of glint positions at an earlier frame can assistdetermining the expected positions of the glints in subsequent frames,because the glints do not move appreciably between the frames when takenat a relatively high frame rate (see, e.g., the glint movements depictedin FIG. 12 ). Such glint imaging enables the eye-tracking system tolimit the frame-by-frame search region to a small number of pixels(e.g., 2 to 10 pixels) around the previous glint positions, whichadvantageously may improve processing speed and efficiency. For example,as described above, only a portion of the glint image (e.g., a 5×5 groupof pixels) may be stored in a temporary memory buffer 615 for processingby an associated CPU 612. Glints that are present in the image portionmay be quickly and efficiently identified and their positionsdetermined. The glint positions may be used for subsequent processing(e.g., with the longer exposure images) and the glint image deleted frommemory.

A further advantage of such glint imaging can be that labeling of eachof the glints is less likely to result in error (e.g., mislabeling theupper left hand glint as the upper right hand glint or the lower lefthand glint), because the eye-tracking system can follow the smallmovements of the glints from frame to frame. For example, the“constellation” of four glints depicted in FIG. 12 may tend to move at asubstantially common velocity from frame to frame as the eye moves. Thecommon velocity may represent an average or mean velocity of theconstellation. Thus, the system can check that all identified glints aremoving at approximately the same velocity. If one (or more) of theglints in the “constellation” moves at a substantially differentvelocity (e.g., more than a threshold amount different from the commonvelocity), then that glint may have been misidentified or the glint mayhave reflected from a non-spherical portion of the cornea.

As such, it follows that small changes in glint position fromframe-to-frame may be relied upon with a relatively high degree ofconfidence, for example, if all four glints exhibit comparable changesin position. As such, in some implementations, the eye tracking module614 may be able to detect saccadic and microsaccadic movements with arelatively high degree of confidence on the basis of as few as two imageframes. For example, in these implementations, the eye tracking modulemay be configured to determine whether a global change in glint positionfrom one frame to the next exceeds a threshold value and, in response todetermining that such a global change does indeed exceed the thresholdvalue, determine that the user’s eye is engaging in saccadic (ormicrosaccadic) movement. This may advantageously be utilized to performdepth plane switching, for example, as described in theabove-incorporated U.S. Patent Application No. 62/660,180 filed Apr. 19,2018 and U.S. Patent Application Publication No. 2019/0324276.

FIG. 13A, which is generally similar to FIG. 8A, illustrates a situationwhere one of the glints is reflected from a non-spherical portion of thecornea. The eye-tracking system can determine the cornea modeled centerof the corneal sphere 1402 from the glints from the light sources 326 aand 326 b. For example, the reflections from the light sources 326 a,326 b can be projected (shown as dashed lines 1302) back to the corneamodeled center 804, where both dashed lines 1302 meet at a common point.However, if the system projects the glint from the light source 326 ctoward the center, dashed line 1304 does not meet at the cornea modeledcenter 804. If the eye-tracking system were to use the glint from thelight source 326 c to attempt to find the center 804 of the cornealsphere 802, error would be introduced to the center position (becausethe line 1304 does not intersect the center 804). Accordingly, bytracking glint positions in the glint images, the system can identify asituation where a glint is likely reflected from a non-spherical regionof the cornea (e.g., because the glint velocity is different from thecommon velocity of the constellation) and remove the glint from thecorneal sphere modeling calculation (or reduce a weight assigned to thatglint). The glint speed of glints in non-spherical corneal regions isoften much faster than the glint speed for spherical regions and thisincrease in speed can be used, at least partly, to identify when a glintis arising from a non-spherical corneal region.

When the user blinks, the user’s eyelid may at least partially cover aportion of the cornea where a light source would reflect from. The glintarising from this region may have a lower intensity or have an imageshape that is substantially non-spherical (which can introduce errorinto determining its position). FIG. 13B is an image that shows anexample of a glint 550 a where there is partial occlusion. Glint imagingcan also be used to identify when a glint becomes at least partiallyoccluded by monitoring the intensities of the glints in the image. Inthe case of no occlusion, each glint may have approximately the sameintensity from frame to frame, whereas if there is at least partialocclusion, the intensity of the glint will rapidly decrease. Thus, theeye-tracking system can monitor the glint intensity as a function oftime (e.g., from frame to frame) to determine when partial or totalocclusion occurs, and remove that glint from the eye-tracking analysis(or reduce a weight assigned to that glint). Further, the constellationof glints may have approximately similar intensities, so the system canmonitor whether there is difference of a particular glint intensity fromthe common intensity of the constellation. In response to such adetermination, the eye-tracking system can remove that glint from theeye-tracking analysis (or reduce a weight assigned to that glint).Alternatively, as described in further detail below with reference toFIG. 20 , in some implementations, the eye-tracking system may estimatethe location of a partially or totally occluded glint.

The glint detection and labeling module 714 described with reference toFIG. 7 thus can advantageously include a glint motion detector tomonitor glint velocity or glint intensity from frame to frame in theglint imaging to provide a more robust determination of glint positions,which can provide a more robust determination of the center of thecorneal sphere (e.g., determined by the 3D cornea center estimationmodule 716 of FIG. 7 ).

Example Glint-Pupil Motion Relationships

The applicant has determined that a relationship exists between movementof glints in eye images and movement of the pupil. FIGS. 14A and 14B aregraphs of examples of glint movement versus pupil movement in aCartesian (x,y) coordinate system, with the x-axis being horizontal andthe y-axis being vertical. FIG. 14A shows the glint x-location (inpixels) versus the pupil x-location (in pixels); FIG. 14B shows theglint y-location (in pixels) versus the pupil y-location (in pixels). Inthese examples, four glints (A, B, C, and D) where tracked, and therewas no movement of the user’s head relative to the eye-tracking (ET)system during measurement. As can be seen from FIGS. 14A and 14B, thereis a strong linear relationship between glint movement and pupilmovement. For example, glint movement has about one-half the speed ofpupil movement. The linear relationship and the particular values of theslopes in FIGS. 14A and 14B may be due to the geometry of theeye-tracking system used for the measurements, and it is expected thatanalogous relationships between glint movement and pupil movement willbe present for other eye-tracking systems (and can be determined byanalysis of eye-tracking images). As mentioned above, in someimplementations, the eye-tracking system may estimate the location of apartially or totally occluded glint. In these implementations, which aredescribed in further detail below with reference to FIG. 20 , theeye-tracking system may leverage a probabilistic statistical model ofsuch a glint-pupil relationship so as to estimate the locations of oneor more partially or totally occluded glints.

The glint-pupil relationship together with the robustness of glintdetermination provided by the glint imaging can be used to providerobustness to the determination of the pupil center (or center ofrotation, CoR). Furthermore, leveraging the glint-pupil relationship todetermine pupil position may advantageously provide computationalsavings of the pupil identification and position determinationtechniques described above with reference to one or more of the modulesof FIG. 7 , such as module 712 or module 720. For example, glintpositions can be robustly determined (e.g., to subpixel accuracy) fromthe glint images and an estimate of the position of the pupil center (orCoR) can be predicted based at least in part on the glint-pupilrelationship (see, e.g., FIGS. 14A and 14B). Over the relatively shortperiods of time that the glint images are captured (e.g., every 2 to 10ms), the pupil center (or CoR) does not change appreciably. Glintpositions can be tracked and averaged over multiple glint frame captures(e.g., from 1 to 10 frames). Using the glint-pupil relationship, theaverage glint position provides the estimate for the pupil position (orCoR). In some embodiments, this estimate can then be used in analysis ofthe longer exposure images to more accurately and reliably determine thepupil center (or CoR). In other embodiments, this estimate, alone, mayserve to inform the system of the pupil center. As such, in at leastsome of these embodiments, the eye tracking module need not rely uponlonger exposure images to determine the pupil center (or CoR). Rather,in such embodiments, the eye tracking module may rely upon longerexposure images for other purposes or, in some examples, may forgo thecapture of such longer exposure images altogether.

Gaze Prediction for Foveated Rendering

As described with reference to FIG. 6 , the render controller 618 canuse information from the eye tracking module 614 to adjust imagesdisplayed to the user by the render engine 622 (e.g., a render enginethat may be a software module in the GPU 620 and that may provide imagesto the display 220 of the wearable system 200). As an example, therender controller 618 may adjust images displayed to the user based onthe user’s center of rotation or center of perspective.

In some systems, pixels in the display 220 are rendered near the gazedirection at a higher resolution or frame rate than in regions of thedisplay 220 away from the gaze direction (which may not be rendered atall in some cases). This is sometimes referred to as foveated renderingand may provide substantial computational performance gains, becauseprimarily substantially only pixels in the gaze direction may berendered. Foveated rendering may provide an increase in renderingbandwidth and a decrease in power consumption by the system 200.Examples of wearable systems 200 that utilize foveated rendering aredescribed in U.S. Patent Publication No. 2018/0275410, entitled “DepthBased Foveated Rendering for Display Systems,” which is herebyincorporated by reference herein in its entirety.

FIG. 15 schematically illustrates an example of foveated rendering. Afield of view (FoV) of a display (e.g., the display 220) with theoriginal location of the gaze direction (also referred to as the fovea)shown as circle 1502. Arrow 1504 represents a fast saccade of the eye(e.g., at about 300 arcminute/sec). The dashed circle 1506 represents aregion of uncertainty where the gaze direction might be in the case of afast saccade. Pixels of the display in the region 1506 may be renderedwhereas pixels of the display outside the region 1506 may not berendered (or rendered at a lower frame rate or resolution). The area ofthe region 1506 increases approximately as the square of the timebetween when the gazes moves to a new direction and when images can beactually rendered by the render pipeline (sometimes referred to as themotion-to-photon timescale). In various embodiments of the wearablesystem 200, the motion-to-photon timescale is in a range from about 10ms to 100 ms. Accordingly, it may be advantageous for the eye-trackingsystem to be able to predict a future gaze direction (out to about themotion-to-photon time for the display) so that the rendering pipelinecan begin generating image data for display when the user’s eyes move tothe future gaze direction. Such prediction of the future gaze directionfor foveated rendering can provide user benefits such as, e.g.,increased apparent responsiveness of the display, reduced latency inimage generation, and so forth.

FIG. 16 schematically illustrates an example timing diagram 1600 for arendering pipeline, which utilizes an embodiment of multiple exposuretime eye imaging for eye tracking. The rendering pipeline is initiallyidle 1602 (awaiting the next glint exposure) and then a glint exposure1604 is captured (the exposure time may be less than 50 µs). The glintimage is read out 1606 by a camera stack, and the readout time can bedecreased by reading out only the peaks of the glint image. Glints andglint positions are extracted at 1608 and the eye-tracking systemdetermines gaze at 1610. The renderer (e.g., render controller 618 andrender engine 622) renders the images for display at 1612.

FIG. 17 is a block diagram of an example gaze prediction system 1700 forfoveated rendering. The system 1700 can be implemented, for example, aspart of the system 600 described with reference to FIGS. 6 and 7 . Thesystem 1700 has two pipelines: an image pipeline for obtaining glintimages and a glint pipeline for processing the glints and predicting afuture gaze direction out to a gaze prediction time. As described abovethe gaze prediction time for foveated rendering may be comparable to themotion-to-photon time for the system 600 (e.g., from 10 ms to 100 ms invarious implementations). For some rendering applications, the gazeprediction time is in a range from about 20 ms to 50 ms, e.g., about 25ms to 30 ms. The blocks show in FIG. 17 are illustrative and in otherembodiments, one or more of the blocks can be combined, reorganized,omitted or additional blocks added to the system 1700.

At block 1702, the system 1700 receives a glint image. An example of aglint image is the image 1004 shown in FIG. 10B, in which peaks of theglints are imaged. At block 1706, the system can threshold the image,e.g., set the intensity values of the lowest image pixel values to be alower threshold (e.g., zero). At block 1710, non-maxima in the glintimage are suppressed or removed, which can assist in finding just theglint peaks. For example, the system 1700 can scan across rows (orcolumns) of the image to find maxima. Continuing at block 1710, closemaxima can be processed to remove the lesser maxima of a group ofclosely spaced maxima (e.g., maxima within a threshold pixel distancefrom each other, e.g., 2 to 20 pixels). For example, a user may wear acontact lens. Reflection of a light source 326 can occur at both thefront of the contact lens and at the cornea, resulting in twoclosely-spaced glints. The non-maxima suppression at block 1710 caneliminate the lesser maxima so that only the primary or first specularreflection is kept for further processing.

The glint pipeline receives the processed glint image from the imagepipeline. Glint tracking and classification (e.g., labeling) can beperformed at block 1714. As described with reference to FIG. 12 ,information on previously identified glints (e.g., position, intensity,etc.) can be received from block 1716, and the block 1714 can use thisinformation to identify a search region in the glint image where each ofthe glints is likely to be found (which may reduce search time andincrease processing efficiency). The previous glint information from theblock 1716 can also be useful in identifying if a glint has been atleast partially occluded or the glint comes from a non-spherical portionof the cornea. Such glints may be removed from glint tracking at block1714. Alternatively, as mentioned above with reference to FIGS. 13B and14A-14B, in some implementations, the eye-tracking system may estimatethe location of a partially or totally occluded glint. Additionaldetails are provided below with reference to FIG. 20 .

At block 1718, the system 1700 computes the current gaze (e.g., the eyeoptical axis or the gaze vector) from the glint information receivedfrom the block 1714. At block 1720, previous gaze information (e.g.,determined from a previous glint image) is input to block 1722 where afuture gaze direction is computed. For example, the system 1700 canextrapolate from the current gaze (block 1718) and one or more previousgazes (block 1720) to predict the gaze at the future gaze time (e.g., 10ms to 100 ms in the future). The predicted gaze from the block 1722 canbe provided to the rendering engine to enable foveated rendering.

In some embodiments, the pipelines in the system 1700 run at the glintimaging high frame rate (e.g., 100 fps to 400 fps).

FIGS. 18A-18D illustrate results of an experiment to predict future gazeusing an embodiment of the gaze prediction system 1700. In this exampleexperiment, the glint image frame rate was 160 fps. FIG. 18A shows theglint path for each of four glints when the user’s eye was moving over afield of view that was about 40 arcminutes by 20 arcminutes. The pathsof the four glints are shown by different filled points, and the path ofthe mean value of these glints is shown by open squares. FIG. 18B showsa comparison of the gaze predictions (short solid lines) versus the path(in open squares) of the mean value of the glints (which is consideredto be the ground truth for this experiment). The future prediction timeis 37.5 ms and glints from up to 18.75 ms in the past were used for theprediction. As can be seen from FIG. 18B, many if not most of thepredictions accurately track the mean path of the eye. FIG. 18C is aplot of eye angular velocity (in degrees per second) versus frames, witha velocity histogram 1820 on the left-hand-side of the figure. FIG. 18Cshows that most of the eye movements occur at relatively low angularvelocities (e.g., below about 25 deg/s) with persistent but somewhatsporadic or random movements up to about 200 deg/s. FIG. 18D is areceiver operating characteristic (ROC) plot showing predictionpercentile versus error between the prediction and the ground truth(GT). The different lines are for different future prediction times from6.25 ms up to 60 ms. The closer a line is to vertical (toward the left),the more accurate the prediction. For prediction times near 6.25 ms(which is the inverse of the frame rate for this experiment), the erroris very small. The error increases as the prediction time gets longer,but even at a prediction time of 50 ms, over 90 percent of the gazepredictions have an error less than 5 pixels.

Example Method for Eye Tracking

FIG. 19 is a flowchart that illustrates an example method 1900 for eyetracking. The method 1900 can be performed by embodiments of thewearable display system 200, 400, or 600, for example, using the eyetracking system 601 described with reference to FIGS. 6 and 7 . Invarious embodiments of the method 1900, the blocks described below canbe performed in any suitable order or sequence, and blocks can becombined or rearranged, or other blocks can be added.

At block 1904, the method 1900 captures a longer exposure image of theeye, for example, using the eye-tracking camera 324. The exposure timeof the longer exposure image may be in a range from 200 µs to 1200 µs,for example, about 700 µs. The exposure time for the longer exposureimage can depend on the properties of the eye tracking camera 324 andcan be different in other embodiments. The exposure time for the longerexposure image should have sufficient dynamic range to capture featuresof the pupil or iris. The longer exposure images can be taken at a framerate in a range from 10 fps to 60 fps in various embodiments.

At block 1908, the method 1900 captures shorter exposure (glint) imageof the eye, for example, using the eye-tracking camera 324. The exposuretime of the glint image may be in a range from 5 µs to 100 µs, forexample, less than about 40 µs. The exposure time for the shorterexposure, glint image may be less than the exposure time for the longerexposure image captured at block 1904. The exposure time for the glintimage can depend on the properties of the eye tracking camera 324 andcan be different in other embodiments. The exposure time for the glintimage should be sufficient to image peaks of the glints from the lightsources 326. The exposure time may be sufficient that the glints are notsaturated and have a width of a few (e.g., 1 to 5) pixels, in order toenable subpixel location of the glint center. The ratio of the exposuretime for the longer exposure image relative to the exposure time for theglint image can be in a range from 5 to 50, 10 to 20, or some otherrange. The glint images can be taken at a frame rate in a range from 100fps to 1000 fps in various embodiments. The ratio of the frame rate forthe glint images relative to the frame rate for the longer exposureimages can be in a range from 1 to 100, 1 to 50, 2 to 20, 3 to 10, orsome other ratio.

At block 1912, the method 1900 (e.g., using the CPU 612) can determinepupil center (or center of rotation, CoR) from the longer exposure imageobtained at block 1904. The method 1900 can analyze the longer exposureimages for other eye features (e.g., an iris code) for other biometricapplications.

At block 1916, the method 1900 (e.g., using the CPU 612) can determineglint positions from the glint image obtained at block 1908. Forexample, the method 1900 can fit a 2-D Gaussian to the glint images todetermine the glint position. Other functionality can be performed atblock 1916. For example, as described with reference to FIG. 17 , themethod 1900 can threshold the glint image, remove non-maxima or closemaxima from the glint image, and so forth. The method 1900 can track a“constellation” of glints and use the mean velocity of the constellationto assist in identifying estimated glint positions, whether a glint isreflected from a non-spherical region of the cornea, is experiencing atleast partial occlusion, and so forth. At block 1916, the method 1900can utilize previously determined positions of glints (e.g., in priorglint images) to assist locating or labeling glints in the current glintimage.

At block 1920, the method 1900 (e.g., using the CPU 612) can determine acurrent gaze using the information determined from the longer exposureimage and the shorter exposure, glint image. For example, the glintpositions obtained from the glint image and the pupil center obtainedfrom the longer exposure image can be used to determine the gazedirection. The gaze direction can be expressed as two angles, forexample, θ (azimuthal deflection, determined from a fiducial azimuth)and ϕ (zenithal deflection, sometimes also referred to as a polardeflection) described with reference to FIG. 5A.

At block 1924, the method 1900 (e.g., using the CPU 612) can predict afuture gaze from the current gaze and one or more previous gazes. Asdescribed with reference to FIGS. 15 to 17 , future gaze can beadvantageously used for foveated rendering. The future gaze can bepredicted via extrapolation techniques. The block 1924 can predict thefuture gaze at a future gaze time (e.g., 10 ms to 100 ms after the timefor which the current gaze is computed).

At block 1928, the method 1900 (e.g., using the render controller 618 orthe render engine 622) can render virtual content for presentation tothe user of the wearable display system. As described above, forfoveated rendering, knowledge of the user’s future gaze direction can beused to more efficiently begin preparing the virtual content forrendering when the user is looking in the future gaze direction, whichmay advantageously reduce latency and improve rendering performance.

In some embodiments, the wearable display system may not utilizefoveated rendering techniques, and the method 1900 may not predictfuture gaze direction. In such embodiments, the block 1924 is optional.

As mentioned above with reference to FIGS. 13B, 14A-14B, and 17 , insome situations, one or more glints may be partially or totally occludedby a user’s eyelids, eyelashes, and the like. In some implementations,the eye-tracking system may estimate the location of a partially ortotally occluded glint. In these implementations, which are described infurther detail below with reference to FIG. 20 , the eye-tracking systemmay leverage a probabilistic statistical model of a glint-pupilrelationship so as to estimate the locations of one or more partially ortotally occluded glints. Such a glint-pupil relationship may, in someexamples, be similar to one or more of the glint-pupil relationshipsdescribed above with reference to FIGS. 14A-14B. In some examples, theeye-tracking system may estimate the locations of one or more partiallyor totally occluded glints in response to determining that less than apredetermined minimum threshold quantity of glints (e.g., two glints)has been detected. In some implementations, the eye-tracking system mayapply the detected glint locations, the determined pupil location, orboth to a probabilistic statistical model of a glint-pupil relationshipto identify regions in an image in which glints are expected to be shownand estimate locations in an image at which glints are expected to beshown. In some examples, the eye-tracking system may use the detectedglint locations together with the estimated glint locations to determineeye pose and/or provide the estimated glint locations along with thedetected glint locations for output to one or more downstream modules.

In some implementations, the probabilistic statistical model that isleveraged by the eye-tracking system for glint location estimation maybe generated and/or adapted for each user. That is, in someimplementations, the eye-tracking system may develop a model of glintlocation as a function of pupil location for a given user based oneye-tracking data obtained for that user (e.g., determined pupillocations and determined glint locations) over a period of time. Asdescribed above with reference to FIGS. 14A-14B, there is anapproximately linear relationship between pupil and glint location. Assuch, the eye-tracking system may develop such a probabilisticstatistical model of the glint-pupil relationship for a given user byperforming linear regression on eye-tracking data obtained for thatuser. In some implementations, the eye-tracking system may recursivelyupdate a linear fit over time, for example, using a least-squareapproach as new eye-tracking data arrives. In some examples, theeye-tracking system may employ one or more Kalman filtering techniquesto update the model over time.

FIG. 20 is a flowchart that illustrates an example method 2000 for glintestimation. The method 2000 can be performed by embodiments of thewearable display system 200, 400, or 600, for example, using the eyetracking system 601 described with reference to FIGS. 6 and 7 . Invarious embodiments of the method 2000, the blocks described below canbe performed in any suitable order or sequence, and blocks can becombined or rearranged, or other blocks can be added or removed or anycombination thereof.

In some implementations, the method 2000 may be performed by ahead-mounted system that includes one or more cameras that areconfigured to capture images of an eye of a user, multiple light sources(e.g., infrared light sources) that are configured to illuminate the eyeof the user in a manner so as to produce glints in images of the eye ofthe user captured by the one or more cameras, and one or more processorscoupled to the one or more cameras. In at least some of suchimplementations, some or all of the operations of method 2000 may beperformed at least in part by the one or more processors of the system.In some examples, the multiple light sources may include three or morelight sources.

At block 2002, the method 2000 may include receiving an image of an eyeof a user. This may, for example, correspond to one or more processorsreceiving an image of from one or more cameras. At block 2004, themethod 2000 may include detecting a set of one or more glints in theimage. For example, at block 2004, one or more of the glint detectiontechniques described herein may be employed to detect locations in theimage at which glints are shown.

At block 2006, the method 2000 may include determining whether thedetected set of one or more glints includes less than a minimum quantityof glints. For example, this may include determining whether thedetected set of one or more glints includes less than two glints.

In response to determining, at block 2006, that the detected set of oneor more glints includes less than the minimum quantity of glints,operations associated with block 2008 may be performed. For instance,the detected set of one or more glints may include less than the minimumquantity of glints as a result of the partial or total occlusion of oneor more glints. At block 2008, the method 2000 may include applying thedetected set of one or more glints to a model to estimate a set of oneor more glints in the image. For example, such a model may correspond toa probabilistic statistical model of the glint-pupil relationship. Insome implementations, such a model may be generated and/or adapted foreach user. For example, the estimated set of one or more glint locationsmay correspond to locations in the image at which one or more glints maybe shown, had they not been partially or totally occluded.

At block 2010, the method 2000 may include determining a pose of the eyebased on the detected set of one or more glints and the estimated set ofone or more glints. Following block 2010, at block 2012, the method 2000may include updating the model based at least in part on the detectedset of one or more glints. For example, this may include updating alinear fit over time, for example, using a least-square approach.

In response to determining, at block 2006, that the detected set of oneor more glints includes at least the minimum quantity of glints,operations associated with block 2011 may be performed. At block 2011,the method 2000 may include determining a pose of the eye based on thedetected set of one or more glints. Following block 2011, at block 2012,the method 2000 may include updating the model based at least in part onthe detected set of one or more glints.

In some implementations, the method 2000 may further include identifyinga location in the image of the eye of the user at which a center of apupil of the eye of the user is shown. In these implementations, atblock 2008, the method 2000 may include applying the identified locationof the center of the pupil and the detected set of one or more glints toa model to estimate a set of one or more glints in the image.

Following block 2012, at block 2002, the method 2000 may includereceiving another image of the eye of the user. Following block 2004 andin response to determining, at block 2006, that the detected set of oneor more glints includes less than the minimum quantity of glints,operations associated with block 2008 may be performed. However, at thisjuncture, such operations associated with block 2008 include applyingthe detected set of one or more glints to the model, as updated at block2012, to estimate a set of one or more glints in the image. Thisrecursion in method 2000 is demonstrative of how the probabilisticstatistical model may possibly be updated for a given user over time.

Additionally, in at least some of these implementations, the method 2000may further include applying the identified location of the center ofthe pupil of the eye of the user to the model to identify a plurality ofregions in the image of the eye of the user at which a plurality ofglints are expected to be shown, respectively. In some examples, suchidentified regions in the image may be similar to one or more of the“search” areas or regions described herein. In such implementations, atblock 2004, the method 2000 may include detecting a set of one or morelocations in one or more of the plurality of identified regions,respectively.

In some of these implementations, at block 2008, the method 2000 mayinclude (i) applying the identified location of the center of the pupilof the eye of the user to the probabilistic statistical model toidentify one or more regions in the image of the eye of the user atwhich one or more glints are expected to be shown, respectively, and(ii) applying the detected set of one or more glint locations to theprobabilistic statistical model to estimate a set of one or morelocations in the one or more identified regions of the image of the eyeof the user at which one or more glints are shown, respectively.

In some of these implementations, at block 2012, the method 2000 mayinclude updating the probabilistic statistical model based on theidentified location of the center of the pupil of the eye of the userand the detected set of one or more glint locations.

In some examples, at 2010, the method 2000 may include determining alocation of a center of a cornea of the eye of the user, a location of acenter of rotation of the eye of the user, and/or a gaze direction ofthe eye of the user based at least in part on the detected set of one ormore glint locations and the estimated set of one or more glintlocations. Accordingly, in various examples, at 2010, the method 2000may include determining one or more quantities associated with the eyeor with the vision of the eye of the user (e.g., the center ofperspective) based at least in part on the detected set of one or moreglint locations and the estimated set of one or more glint locations.

EXAMPLES

Example 1. A head-mounted system comprising:

-   one or more cameras configured to capture images of an eye of a    user;-   a plurality of light sources configured to illuminate the eye of the    user in a manner so as to produce glints in images of the eye of    user captured by the one or more cameras, wherein a total quantity    of light sources included in the plurality of light sources is    greater than or equal to a particular value; and-   one or more processors operatively coupled to the one or more    cameras, the one or more processors configured to:    -   receive an image of the eye of the user from the one or more        cameras;    -   detect a set of one or more locations in the image of the eye of        the user at which one or more glints are shown, respectively;    -   determine whether a total quantity of locations included in the        detected set of one or more glint locations is less than the        particular value;    -   in response to a determination that the total quantity of        locations included in the detected set of one or more glint        locations is less than the particular value:        -   apply the detected set of one or more glint locations to a            probabilistic statistical model to estimate a set of one or            more locations in the image of the eye of the user at which            one or more glints are shown, respectively, the estimated            set of one or more glint locations being different from the            detected set of one or more glint locations; and        -   determine a pose of the eye of the user based at least in            part on the detected set of one or more glint locations and            the estimated set of one or more glint locations.

Example 2. The system of Example 1, wherein the one or more processorsare further configured to:

-   identify a location in the image of the eye of the user at which a    center of a pupil of the eye of the user is shown;-   wherein to apply the detected set of one or more glint locations to    a probabilistic statistical model to estimate the set of one or more    locations in the image of the eye of the user at which one or more    glints are shown, respectively, the one or more processors are    configured to:    -   apply the identified location of the center of the pupil of the        eye of the user and the detected set of one or more glint        locations to the probabilistic statistical model to estimate the        set of one or more locations in the image of the eye of the user        at which one or more glints are shown, respectively.

Example 3. The system of Example 2, wherein the one or more processorsare further configured to:

-   apply the identified location of the center of the pupil of the eye    of the user to the probabilistic statistical model to identify a    plurality of regions in the image of the eye of the user at which a    plurality of glints are expected to be shown, respectively, wherein    a total quantity of regions included in the plurality of identified    regions is greater than or equal to the particular value; and-   wherein to detect the set of one or more locations in the image of    the eye of the user at which one or more glints are shown,    respectively, the one or more processors are configured to:    -   detect a set of one or more locations in one or more of the        plurality of identified regions, respectively.

Example 4. The system of Example 2 or 3, wherein to apply the identifiedlocation of the center of the pupil of the eye of the user and thedetected set of one or more glint locations to the probabilisticstatistical model to estimate the set of one or more locations in theimage of the eye of the user at which one or more glints are shown,respectively, the one or more processors are configured to:

-   apply the identified location of the center of the pupil of the eye    of the user to the probabilistic statistical model to identify one    or more regions in the image of the eye of the user at which one or    more glints are expected to be shown, respectively; and-   apply the detected set of one or more glint locations to the    probabilistic statistical model to estimate a set of one or more    locations in the one or more identified regions of the image of the    eye of the user at which one or more glints are shown, respectively.

Example 5. The system of any of Examples 2-4, wherein the one or moreprocessors are further configured to: update the probabilisticstatistical model based on the identified location of the center of thepupil of the eye of the user and the detected set of one or more glintlocations.

Example 6. The system of any of the Examples above, wherein theparticular value corresponds to a value of two.

Example 7. The system of Example 6, wherein the total quantity of lightsources included in the plurality of light sources is greater than orequal to a value of three.

Example 8. The system of any of the Examples above, wherein theplurality of light sources comprise a plurality of infrared lightsources.

Example 9. The system of any of the Examples above, wherein to determinethe pose of the eye of the user based at least in part on the detectedset of one or more glint locations and the estimated set of one or moreglint locations, the one or more processors are configured to:

determine a location of a center of a cornea of the eye of the userbased at least in part on the detected set of one or more glintlocations and the estimated set of one or more glint locations.

Example 10. The system of any of the Examples above, wherein todetermine the pose of the eye of the user based at least in part on thedetected set of one or more glint locations and the estimated set of oneor more glint locations, the one or more processors are configured to:

determine a location of a center of rotation of the eye of the userbased at least in part on the detected set of one or more glintlocations and the estimated set of one or more glint locations.

Example 11. The system of any of the Examples above, wherein todetermine the pose of the eye of the user based at least in part on thedetected set of one or more glint locations and the estimated set of oneor more glint locations, the one or more processors are configured to:

determine a gaze direction of the eye of the user based at least in parton the detected set of one or more glint locations and the estimated setof one or more glint locations.

Example 12. The system of any of the Examples above, wherein the one ormore processors are further configured to:

-   in response to a determination that the total quantity of locations    included in the detected set of one or more glint locations is    greater than the particular value:    -   determine a pose of the eye of the user based at least in part        on the detected set of one or more glint locations.

ADDITIONAL EXAMPLES

Example 1. A head-mounted system comprising:

-   one or more cameras configured to capture images of an eye of a    user;-   one or more light sources configured to illuminate the eye of the    user in a manner so as to produce a plurality of glints in images of    the eye of the user captured by the one or more cameras; and-   one or more processors operatively coupled to the one or more    cameras, the one or more processors configured to:    -   receive one or more images of the eye of the user from the one        or more cameras;    -   detect one or more glints and determine respective locations        associated with said one or more detected glints;    -   determine whether a total quantity of glints included in the one        or more detected glints is less than an expected number of        glints;    -   in response to a determination that the total quantity of glints        in the one or more detected glint is less than the expected        number of glints:        -   estimate one or more locations for one or more respective            glints different than said one or more detected glints, the            estimated one or more glint locations being different from            the locations associated with the detected one or more            glints; and        -   determine a pose of the eye of the user based at least in            part on the locations associated with said one or more            detected glints and the estimated one or more glint            locations.

Example 2: The system of Example 1, wherein said one or more lightsources comprises a plurality of light sources.

Example 3. The system of Example 2, wherein respective ones of saidlight sources form corresponding glints.

Example 4. The system of any of Examples 1-3, wherein the one or morelight sources comprise one or more infrared light sources.

Example 5. The system of any of the Examples above, wherein determiningthe total quantity of glints included in said one or more detectedglints comprises determining the total quantity of glint locationsincluded in the one or more determined locations associated with saidone or more detected glints.

Example 6. The system of any of the Examples above, wherein estimatingone or more locations for one or more respective glints different thansaid one or more detected glints comprises applying the respectivelocations associated with the detected one or more glints to aprobabilistic statistical model.

Example 7. The system of any of the Examples above, wherein the one ormore processors are further configured to identify a location associatedwith a center of a pupil of the eye of the user.

Example 8. The system of Example 7, wherein said one or more processorsare configured to use the identified location associated with the centerof the pupil of the eye of the user and the respective glint locationsassociated with the one or more detected glints to provide saidestimated one or more locations for one or more respective glintsdifferent than said one or more detected glints.

Example 9. The system of Example 7 or 8, wherein said one or moreprocessors are configured to apply the identified location associatedwith the center of the pupil of the eye of the user and the respectiveglint locations associated with the one or more detected glints to aprobabilistic statistical model to provide said estimated one or morelocations for one or more respective glints different than said one ormore detected glints.

Example 10. The system of any of the Examples above, wherein said one ormore processors are further configured to identify a plurality ofregions in the image of the eye of the user at which a plurality ofrespective glints are expected to be shown.

Example 11. The system of Example 10, wherein a total quantity of saidregions included in the plurality of identified regions is greater thanor equal to the expected number of glints.

Example 12. The system of Example 10 or 11, wherein to determinerespective locations associated with said one or more detected glints,the one or more processors are configured to determine one or morerespective locations in one or more of the plurality of identifiedregions.

Example 13. The system of Example 12, wherein to determine respectivelocations associated with said one or more detected glints, the one ormore processors are configured to use the identified location of thecenter of the pupil of the eye.

Example 14. The system of Example 12, wherein to determine respectivelocations associated with said one or more detected glints, the one ormore processors are configured to apply the identified location of thecenter of the pupil of the eye of the user to a probabilisticstatistical model.

Example 15. The system of any of Examples 7-9, wherein using theidentified location of the center of the pupil of the eye of the userand the respective locations associated with the one or more detectedglints to estimate the one or more locations for one or more respectiveglints different than said one or more detected glints, the one or moreprocessors are configured to use the identified location of the centerof the pupil to identify one or more regions at which one or morerespective glints are expected and to estimate one or more locations ofthe one or more respective glints different than said one or moredetected glints in the one or more identified regions.

Example 16. The system of any of Examples 7-9 and 15, wherein theidentified location of the center of the pupil of the eye of the userand the respective locations associated with the one or more detectedglints are applied to the probabilistic statistical model to estimatethe one or more locations for one or more respective glints differentthan said one or more detected glints, the one or more processors beingconfigured to apply the identified location of the center of the pupilof the eye of the user to the probabilistic statistical model toidentify one or more regions at which one or more respective glints areexpected, and to apply the one or more respective locations associatedwith the one or more detected glints to the probabilistic statisticalmodel to estimate one or more locations in the one or more identifiedrespective regions.

Example 17. The system of any of the Examples 6, 9, 14, and 16, whereinthe one or more processors are further configured to update theprobabilistic statistical model based on the respective locationsassociated with the one or more detected glints.

Example 18. The system of any of the Examples 6, 9, 14, 16, and 17,wherein the one or more processors are further configured to update theprobabilistic statistical model based on the identified location of thecenter of the pupil of the eye of the user.

Example 19. The system of any of the Examples above, wherein the totalquantity of light sources included in the plurality of light sourcescomprises two.

Example 20. The system of any of the Examples above, wherein the totalquantity of light sources included in the plurality of light sources isgreater than or equal to a value of three.

Example 21. The system of any of the Examples above, wherein thedetected number of glints is two.

Example 22. The system of any of the Examples above, wherein theexpected number of glints is greater than or equal to a value of three.

Example 23. The system of any of the Examples above, wherein todetermine the pose of the eye of the user based at least in part on therespective locations associated with the one or more detected glints andthe estimated one or more locations for one or more respective glintsdifferent than said one or more detected glints, the one or moreprocessors are configured to determine a location of a center of acornea of the eye of the user based at least in part on the respectivelocations associated with the one or more detected glints and theestimated one or more glint locations.

Example 24. The system of any of the Examples above, wherein todetermine the pose of the eye of the user based at least in part on therespective locations associated with the one or more detected glints andthe estimated one or more locations for one or more respective glintsdifferent than said one or more detected glints, the one or moreprocessors are configured to determine a location of a center ofrotation of the eye of the user based at least in part on the respectivelocations associated with the one or more detected glints and theestimated one or more glint locations.

Example 25. The system of any of the Example above, wherein to determinethe pose of the eye of the user based at least in part on the respectivelocations associated with the one or more detected glints and theestimated one or more locations for one or more respective glintsdifferent than said one or more detected glints, the one or moreprocessors are configured to determine a gaze direction of the eye ofthe user based at least in part on the locations associated with the oneor more detected glints and the estimated one or more glint locations.

Example 26. The system of any of the Examples above, wherein the one ormore processors are further configured to, in response to adetermination that the total quantity of glint locations included in thedetermined locations associated with said one or more detected glints isgreater than a particular value, determine a pose of the eye of the userbased at least in part on the determined locations associated with saidone or more detected glints.

Example 27. The system of any of the Examples above, wherein determiningrespective locations associated of said one or more detected glintscomprises determining one or more locations in the image of the eye ofthe user at which one or more respective glints are shown.

Example 28. The system of any of the Examples above, wherein estimatingone or more locations for one or more respective glints comprisesestimating one or more locations in the image of the eye of the user atwhich one or more respectively glints are shown.

Example 29. The system of any of the Examples above, wherein thedetermining respective locations associated of said one or more detectedglints comprises determining a set of one or more locations in the imageof the eye of the user at which one or more glints are shown,respectively.

Example 30. The system of any of the Examples above, wherein estimatingone or more locations for one or more respective glints comprisesestimating a set of one or more locations in the image of the eye of theuser at which one or more glints are shown, respectively.

Example 31. The system of any of the Examples above, wherein identifyinga location associated with a center of a pupil of the eye of the usercomprises identifying a location in the image of the eye of the user atwhich a center of a pupil of the eye of the user is shown.

Example 32. The system of any of the Examples above, wherein todetermine the pose of the eye of the user based at least in part on therespective locations associated with the one or more detected glints andthe estimated one or more locations for one or more respective glintsdifferent than said one or more detected glints, the one or moreprocessors are configured to determine a location of a center ofperspective of the eye of the user based at least in part on respectivelocations associated with the one or more detected glints and theestimated one or more glint locations.

Example 33. The system of any of the Examples above, wherein thelocations associated with said one or more detected glints comprise thelocations of said one or more detected glints.

Example 34. The system of any of the Examples above, wherein thelocations associated with said one or more detected glints comprise thelocations of said one or more detected glints in one or more images ofan eye of a user.

Example 35. The system of any of the Examples above, wherein thehead-mounted system comprise a head-mounted display configured topresent virtual content by outputting light to an eye of a wearer of thehead-mounted display.

Example 36. The system of any of the Examples above, wherein thehead-mounted system comprises an augmented reality head-mounted display.

Example 37. The system of any of the Examples above, wherein theexpected number of glints corresponds to the number of light sources.

Examples Related to U.S. Patent Application No. 16/751076 (AttorneyDocket MLEAP.224A / ML-0592US)

Example 1. A wearable display system comprising:

-   a head-mounted display configured to present virtual content by    outputting light to an eye of a wearer of the head-mounted display;-   a light source configured to direct light toward the eye of the    wearer;-   an eye-tracking camera configured to capture:    -   first images of the eye of the wearer captured at a first frame        rate and a first exposure time; and    -   second images of the eye of the wearer captured at a second        frame rate greater than or equal to the first frame rate and at        a second exposure time less than the first exposure time; and    -   a hardware processor communicatively coupled to the head-mounted        display and the eye-tracking camera, the hardware processor        programmed to:        -   analyze the first images to determine a center of a pupil of            the eye;        -   analyze the second images to determine a position of a            reflection of the light source from the eye;        -   determine, from the center of the pupil and the position of            the reflection, a gaze direction of the eye;        -   estimate, from the gaze direction and previous gaze            direction data, a future gaze direction of the eye at a            future gaze time; and        -   cause the head-mounted display to present the virtual            content at the future gaze time based at least partly on the            future gaze direction.

Example 2. The wearable display system of example 1, wherein the lightsource comprises an infrared light source.

Example 3. The wearable display system of example 1 or example 2,wherein the hardware processor is programmed to analyze the first imagesor the second images to determine a center of rotation or a center ofperspective of the eye of the wearer.

Example 4. The wearable display system of any one of examples 1 to 3,wherein to analyze the second images, the hardware processor isprogrammed to: apply a threshold to the second images, identifynon-maxima in the second images, or suppress or remove non-maxima in thesecond images.

Example 5. The wearable display system of any one of examples 1 to 4,wherein to analyze the second images, the hardware processor isprogrammed to identify a search region for the reflection of the lightsource in a current image from the second images based at least partlyon a position of the reflection of the light source in a previous imagefrom the second images.

Example 6. The wearable display system of any one of examples 1 to 5,wherein to analyze the second images, the hardware processor isprogrammed to:

-   determine a common velocity of a plurality of reflections of the    light source; and-   determine whether a velocity of the reflection of the light source    is different from the common velocity by more than a threshold    amount.

Example 7. The wearable display system of any one of examples 1 to 6,wherein to analyze the second images, the hardware processor isprogrammed to determine whether the reflection of the light source isfrom a non-spherical portion of the cornea of the eye.

Example 8. The wearable display system of any one of examples 1 to 7,wherein to analyze the second images, the hardware processor isprogrammed to identify existence of at least partial occlusion of thereflection of the light source.

Example 9. The wearable display system of any one of examples 1 to 8,wherein the hardware processor is programmed to determine an estimatedposition of the center of the pupil based at least partly on theposition of the reflection of the light source and a glint-pupilrelationship.

Example 10. The wearable display system of example 9, wherein theglint-pupil relationship comprises a linear relationship between glintposition and pupil center position.

Example 11. The wearable display system of any one of examples 1 to 10,wherein the first exposure time is in a range from 200 µs to 1200 µs.

Example 12. The wearable display system of any one of examples 1 to 11,wherein the first frame rate is in a range from 10 frames per second to60 frames per second.

Example 13. The wearable display system of any one of examples 1 to 12,wherein the second exposure time is in a range from 5 µs to 100 µs.

Example 14. The wearable display system of any one of examples 1 to 13,wherein the second frame rate is in a range from 100 frames per secondto 1000 frames per second.

Example 15. The wearable display system of any one of examples 1 to 14,wherein a ratio of the first exposure time to the second exposure timeis in a range from 5 to 50.

Example 16. The wearable display system of any one of examples 1 to 15,wherein a ratio of the second frame rate to the first frame rate is in arange from 1 to 100.

Example 17. The wearable display system of any one of examples 1 to 16,wherein the future gaze time is in a range from 5 ms to 100 ms.

Example 18. The wearable display system of any one of examples 1 to 17,wherein the hardware processor comprises:

-   a first hardware processor disposed on a non-head-mounted component    of the wearable display system; and-   a second hardware processor disposed in or on the head-mounted    display,-   wherein the first hardware processor is utilized to analyze the    first images, and-   wherein the second hardware processor is utilized to analyze the    second images.

Example 19. The wearable display system of example 18, wherein thesecond hardware processor includes or is associated with a memory bufferconfigured to store at least a portion of each of the second images, andwherein the second hardware processor is programmed to delete the atleast a portion of each of the second images after the determination ofthe position of the reflection of the light source from the eye.

Example 20. The wearable display system of any one of examples 1 to 19,wherein the hardware processor is programmed not to combine the firstimages with the second images.

Example 21. A method for eye tracking, the method comprising:

-   capturing, by an eye-tracking camera, first images of an eye at a    first frame rate and a first exposure time;-   capturing, by an eye-tracking camera, second images of the eye at a    second frame rate greater than or equal to the first frame rate and    at a second exposure time less than the first exposure time;-   determining, at least from the first images, a center of a pupil of    the eye;-   determining, at least from the second images, a position of a    reflection of a light source from the eye; and-   determining, from the center of the pupil and the position of the    reflection, a gaze direction of the eye.

Example 22. The method of example 21, further comprising causing adisplay to render virtual content based at least partly on the gazedirection.

Example 23. The method of example 21 or example 22, further comprisingestimating, based at least in part on the gaze direction and previousgaze direction data, a future gaze direction at a future gaze time.

Example 24. The method of example 23, further comprising causing adisplay to render virtual content based at least partly on the futuregaze direction.

Example 25. The method of any one of examples 21 to 24, wherein thefirst exposure time is in a range from 200 µs to 1200 µs.

Example 26. The method of any one of examples 21 to 25, wherein thefirst frame rate is in a range from 10 frames per second to 60 framesper second.

Example 27. The method of any one of examples 21 to 26, wherein thesecond exposure time is in a range from 5 µs to 100 µs.

Example 28. The method of any one of examples 21 to 27, wherein thesecond frame rate is in a range from 100 frames per second to 1000frames per second.

Example 29. The method of any one of examples 21 to 28, wherein a ratioof the first exposure time to the second exposure time is in a rangefrom 5 to 50.

Example 30. The method of any one of examples 21 to 29, wherein a ratioof the second frame rate to the first frame rate is in a range from 1 to100.

Example 31. A wearable display system comprising:

-   a head-mounted display configured to present virtual content by    outputting light to an eye of a wearer of the head-mounted display;-   a light source configured to direct light toward the eye of the    wearer;-   an eye-tracking camera configured to capture images of the eye of    the wearer, the eye tracking camera configured to alternatingly:-   capture first images at a first exposure time; and-   capture second images at a second exposure time less than the first    exposure time; and-   a plurality of electronic hardware components, at least one of which    comprises a hardware processor communicatively coupled to the    head-mounted display, the eye-tracking camera, and at least one    other electronic hardware component in the plurality of electronic    hardware components, wherein the hardware processor programmed is    to:    -   receive and relay each first image of the eye of the wearer        captured by the eye-tracking camera at the first exposure time        to the at least one other electronic hardware component;    -   receive and store pixels of each second image of the eye of the        wearer captured by the eye-tracking camera at the second        exposure time to a buffer;    -   analyze the pixels stored in the buffer to identify locations at        which reflections of the light source are present in each second        image of the eye of the wearer captured by the eye-tracking        camera at the second exposure time; and    -   transmit location data indicating the locations to the at least        one other electronic hardware component;-   wherein the at least one other electronic hardware component is    configured to:    -   analyze each first image of the eye of the wearer captured by        the eye-tracking camera at the first exposure time to identify a        location of a center of a pupil of the eye; and    -   determine, from the location of the center of the pupil and the        location data received from the hardware processor, a gaze        direction of the eye of the wearer.

Example 32. The wearable display system of example 31, wherein the firstexposure time is in a range from 200 µs to 1200 µs.

Example 33. The wearable display system of example 31 or example 32,wherein the second exposure time is in a range from 5 µs to 100 µs.

Example 34. The wearable display system of any one of example 31 to 33,wherein the eye-tracking camera is configured to capture the firstimages at a first frame rate that is in a range from 10 frames persecond to 60 frames per second.

Example 35. The wearable display system of any one of examples 31 to 34,wherein the eye-tracking camera is configured to capture the secondimages at a second frame rate that is in a range from 100 frames persecond to 1000 frames per second.

Example 36. The wearable display system of any one of examples 31 to 35,wherein a ratio of the first exposure time to the second exposure timeis in a range from 5 to 50.

Example 37. The wearable display system of any one of examples 31 to 36,wherein the at least one other electronic hardware component is disposedin or on a non-head-mounted component of the wearable display system.

Example 38. The wearable display system of example 37, wherein thenon-head-mounted component comprises a beltpack.

Example 39. The wearable display system of any one of examples 31 to 38,wherein the pixels of each second image of the eye comprise fewer thanall of the pixels of each second image.

Example 40. The wearable display system of any one of examples 31 to 39,wherein the pixels comprise an n x m array of pixels, wherein each of nand m is an integer in a range from 1 to 20.

Example 41. The wearable display system of any one of examples 31 to 40,wherein the plurality of electronic hardware components are furtherconfigured to:

-   estimate, from the gaze direction and previous gaze direction data,    a future gaze direction of the eye at a future gaze time; and-   cause the head-mounted display to present virtual content at the    future gaze time based at least partly on the future gaze direction.

Example 42. The wearable display system of any one of examples 31 to 41,wherein the hardware processor is programmed to: apply a threshold tothe pixels stored in the buffer, identify non-maxima in the pixelsstored in the buffer, or suppress or remove non-maxima in the pixelsstored in the buffer.

Example 43. The wearable display system of any one of examples 31 to 42,wherein the hardware processor is programmed to:

-   determine a common velocity of the reflections of the light source;    and-   determine whether a velocity of a reflection of the light source is    different from the common velocity by more than a threshold amount.

Example 44. The wearable display system of any one of examples 31 to 43,wherein the hardware processor is programmed to determine whether thelocation of the reflection of the light source is from a non-sphericalportion of the cornea of the eye.

Example 45. The wearable display system of any one of examples 31 to 44,wherein the hardware processor is programmed to identify existence of atleast partial occlusion of the reflection of the light source.

Example 46. The wearable display system of any one of examples 31 to 45,wherein the at least one other electronic hardware component isprogrammed to identify the location of the center of the pupil based atleast partly on the location of the reflection of the light source and aglint-pupil relationship.

Additional Considerations

Each of the processes, methods, and algorithms described herein and/ordepicted in the attached figures may be embodied in, and fully orpartially automated by, code modules executed by one or more physicalcomputing systems, hardware computer processors, application-specificcircuitry, and/or electronic hardware configured to execute specific andparticular computer instructions. For example, computing systems caninclude general purpose computers (e.g., servers) programmed withspecific computer instructions or special purpose computers, specialpurpose circuitry, and so forth. A code module may be compiled andlinked into an executable program, installed in a dynamic link library,or may be written in an interpreted programming language. In someimplementations, particular operations and methods may be performed bycircuitry that is specific to a given function.

Further, certain implementations of the functionality of the presentdisclosure are sufficiently mathematically, computationally, ortechnically complex that application-specific hardware or one or morephysical computing devices (utilizing appropriate specialized executableinstructions) may be necessary to perform the functionality, forexample, due to the volume or complexity of the calculations involved orto provide results substantially in real-time. For example, animationsor video may include many frames, with each frame having millions ofpixels, and specifically programmed computer hardware is necessary toprocess the video data to provide a desired image processing task orapplication in a commercially reasonable amount of time. Additionally,real-time eye-tracking for an AR, MR, VR wearable device iscomputationally challenging, and the multiple exposure time eye trackingtechniques may utilize efficient CPUs, GPUs, ASICs, or FPGAs.

Code modules or any type of data may be stored on any type ofnon-transitory computer-readable medium, such as physical computerstorage including hard drives, solid state memory, random access memory(RAM), read only memory (ROM), optical disc, volatile or non-volatilestorage, combinations of the same and/or the like. The methods andmodules (or data) may also be transmitted as generated data signals(e.g., as part of a carrier wave or other analog or digital propagatedsignal) on a variety of computer-readable transmission mediums,including wireless-based and wired/cable-based mediums, and may take avariety of forms (e.g., as part of a single or multiplexed analogsignal, or as multiple discrete digital packets or frames). The resultsof the disclosed processes or process steps may be stored, persistentlyor otherwise, in any type of non-transitory, tangible computer storageor may be communicated via a computer-readable transmission medium.

Any processes, blocks, states, steps, or functionalities in flowdiagrams described herein and/or depicted in the attached figures shouldbe understood as potentially representing code modules, segments, orportions of code which include one or more executable instructions forimplementing specific functions (e.g., logical or arithmetical) or stepsin the process. The various processes, blocks, states, steps, orfunctionalities can be combined, rearranged, added to, deleted from,modified, or otherwise changed from the illustrative examples providedherein. In some embodiments, additional or different computing systemsor code modules may perform some or all of the functionalities describedherein. The methods and processes described herein are also not limitedto any particular sequence, and the blocks, steps, or states relatingthereto can be performed in other sequences that are appropriate, forexample, in serial, in parallel, or in some other manner. Tasks orevents may be added to or removed from the disclosed exampleembodiments. Moreover, the separation of various system components inthe implementations described herein is for illustrative purposes andshould not be understood as requiring such separation in allimplementations. It should be understood that the described programcomponents, methods, and systems can generally be integrated together ina single computer product or packaged into multiple computer products.Many implementation variations are possible.

The processes, methods, and systems may be implemented in a network (ordistributed) computing environment. Network environments includeenterprise-wide computer networks, intranets, local area networks (LAN),wide area networks (WAN), personal area networks (PAN), cloud computingnetworks, crowd-sourced computing networks, the Internet, and the WorldWide Web. The network may be a wired or a wireless network or any othertype of communication network.

The systems and methods of the disclosure each have several innovativeaspects, no single one of which is solely responsible or required forthe desirable attributes disclosed herein. The various features andprocesses described above may be used independently of one another, ormay be combined in various ways. All possible combinations andsubcombinations are intended to fall within the scope of thisdisclosure. Various modifications to the implementations described inthis disclosure may be readily apparent to those skilled in the art, andthe generic principles defined herein may be applied to otherimplementations without departing from the spirit or scope of thisdisclosure. Thus, the claims are not intended to be limited to theimplementations shown herein, but are to be accorded the widest scopeconsistent with this disclosure, the principles and the novel featuresdisclosed herein.

Certain features that are described in this specification in the contextof separate implementations also can be implemented in combination in asingle implementation. Conversely, various features that are describedin the context of a single implementation also can be implemented inmultiple implementations separately or in any suitable subcombination.Moreover, although features may be described above as acting in certaincombinations and even initially claimed as such, one or more featuresfrom a claimed combination can in some cases be excised from thecombination, and the claimed combination may be directed to asubcombination or variation of a subcombination. No single feature orgroup of features is necessary or indispensable to each and everyembodiment.

Conditional language used herein, such as, among others, “can,” “could,”“might,” “may,” “e.g.,” and the like, unless specifically statedotherwise, or otherwise understood within the context as used, isgenerally intended to convey that certain embodiments include, whileother embodiments do not include, certain features, elements and/orsteps. Thus, such conditional language is not generally intended toimply that features, elements and/or steps are in any way required forone or more embodiments or that one or more embodiments necessarilyinclude logic for deciding, with or without author input or prompting,whether these features, elements and/or steps are included or are to beperformed in any particular embodiment. The terms “comprising,”“including,” “having,” and the like are synonymous and are usedinclusively, in an open-ended fashion, and do not exclude additionalelements, features, acts, operations, and so forth. Also, the term “or”is used in its inclusive sense (and not in its exclusive sense) so thatwhen used, for example, to connect a list of elements, the term “or”means one, some, or all of the elements in the list. In addition, thearticles “a,” “an,” and “the” as used in this application and theappended claims are to be construed to mean “one or more” or “at leastone” unless specified otherwise.

As used herein, a phrase referring to “at least one of” a list of itemsrefers to any combination of those items, including single members. Asan example, “at least one of: A, B, or C” is intended to cover: A, B, C,A and B, A and C, B and C, and A, B, and C. Conjunctive language such asthe phrase “at least one of X, Y and Z,” unless specifically statedotherwise, is otherwise understood with the context as used in generalto convey that an item, term, etc. may be at least one of X, Y or Z.Thus, such conjunctive language is not generally intended to imply thatcertain embodiments require at least one of X, at least one of Y and atleast one of Z to each be present.

Similarly, while operations may be depicted in the drawings in aparticular order, it is to be recognized that such operations need notbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. Further, the drawings may schematically depict one more exampleprocesses in the form of a flowchart. However, other operations that arenot depicted can be incorporated in the example methods and processesthat are schematically illustrated. For example, one or more additionaloperations can be performed before, after, simultaneously, or betweenany of the illustrated operations. Additionally, the operations may berearranged or reordered in other implementations. In certaincircumstances, multitasking and parallel processing may be advantageous.Moreover, the separation of various system components in theimplementations described above should not be understood as requiringsuch separation in all implementations, and it should be understood thatthe described program components and systems can generally be integratedtogether in a single software product or packaged into multiple softwareproducts. Additionally, other implementations are within the scope ofthe following claims. In some cases, the actions recited in the claimscan be performed in a different order and still achieve desirableresults.

What is claimed is:
 1. A method for determining a pose of an eye of auser of a head-mounted system, the method comprising: receiving one ormore images of the eye of the user, the one or more images captured byone or more cameras of the head-mounted system; detecting one or moreglints captured in the one or more images, wherein the one or moreglints are produced through an illumination of the eye by one or morelight sources of the head-mounted system; determining respectivelocations associated with the one or more detected glints; determiningwhether a total quantity of glints included in the one or more detectedglints is less than an expected number of glints; in response to adetermination that the total quantity of glints in the one or moredetected glints is less than an expected number of glints: estimatingone or more locations for one or more respective glints different thanthe one or more detected glints, the estimated one or more glintlocations being different from the locations associated with thedetected one or more glints; and determining the pose of the eye of theuser based at least in part on the locations associated with the one ormore detected glints and the estimated one or more glint locations. 2.The method of claim 1, wherein determining the total quantity of glintsincluded in the one or more detected glints includes determining thetotal quantity of glint locations included in the one or more determinedlocations associated with the one or more detected glints.
 3. The methodof claim 1, further comprising: identifying a location associated with acenter of a pupil of the eye of the user.
 4. The method of claim 3,wherein estimating the one or more locations for one or more respectiveglints is based at least partly on the identified location associatedwith the center of the pupil of the eye of the user and the respectiveglint locations associated with the one or more detected glints.
 5. Themethod of claim 1, further comprising: identifying a plurality ofregions in the one or more images of the eye of the user at which aplurality of respective glints are expected to be shown.
 6. The methodof claim 5, wherein a total quantity of the regions included in theplurality of identified regions is greater than or equal to the expectednumber of glints.
 7. The method of claim 5, wherein determiningrespective locations associated with the one or more detected glintsincludes determining one or more respective locations in one or more ofthe plurality of identified regions.
 8. The method of claim 7, whereindetermining respective locations associated with the one or moredetected glints is based at least partly on an identified location of acenter of a pupil of the eye.
 9. The method of claim 4, whereinestimating one or more locations of the one or more respective glintsincludes: using the identified location associated with the center ofthe pupil to identify one or more regions in which one or morerespective glints are expected; and estimating the one or more locationsof the one or more respective glints in the one or more identifiedregions.
 10. The method of claim 1, wherein determining the pose of theeye of the user includes determining a location of a center of a corneaof the eye of the user based at least in part on the respectivelocations associated with the one or more detected glints and theestimated one or more glint locations.
 11. The method of claim 1,wherein determining the pose of the eye of the user includes determininga location of a center of rotation of the eye of the user based at leastin part on the respective locations associated with the one or moredetected glints and the estimated one or more glint locations.
 12. Themethod of claim 1, wherein determining the pose of the eye of the userincludes determining a gaze direction of the eye of the user based atleast in part on the locations associated with the one or more detectedglints and the estimated one or more glint locations.
 13. The method ofclaim 1, further comprising: in response to a determination that thetotal quantity of glint locations included in the determined locationsassociated with the one or more detected glints is greater than aparticular value, determining the pose of the eye of the user based atleast in part on the determined locations associated with the one ormore detected glints.
 14. The method of claim 1, wherein determiningrespective locations associated of the one or more detected glintscomprises determining one or more locations in the one or more images ofthe eye of the user at which one or more respective glints are shown.15. The method of claim 1, wherein estimating one or more locations forone or more respective glints comprises estimating one or more locationsin the one or more images of the eye of the user at which one or morerespectively glints are shown.
 16. The method of claim 1, whereindetermining the pose of the eye of the user includes determining alocation of a center of perspective of the eye of the user based atleast in part on respective locations associated with the one or moredetected glints and the estimated one or more glint locations.
 17. Themethod of claim 1, wherein estimating one or more locations for one ormore respective glints different than the one or more detected glints isbased at least partly on applying the determined one or more glintlocations to a probabilistic statistical model.
 18. The method of claim1, wherein the expected number of glints is two.
 19. The method of claim1, wherein the one or more light sources include at least one infraredlight source.
 20. The method of claim 1, wherein the one or more lightsources include at least three light sources.